Project

Smart grid,Microgrid

Goal: optimization,GA,BPSO,WDO,ACO,appliances scheduling,hybrid power generation,solar PV and diesel generator

Updates
0 new
7
Recommendations
0 new
1
Followers
0 new
81
Reads
0 new
677

Project log

Qazi Zafar Iqbal
added 3 research items
In this paper, an efficient model based on factored conditional restricted boltzmann machine (FCRBM) is proposed for electric load forecasting of in smart grid (SG). This FCRBM has deep layers structure and uses rectified linear unit (RELU) function and multivariate autoregressive algorithm for training. The proposed model predicts day ahead and week ahead electric load for decision making of the SG. The proposed model is a hybrid model having four modules i.e., data processing and features selection module, FCRBM based forecaster module, GWDO (genetic wind driven optimization) algorithm-based optimizer module, and utilization module. The proposed model is examined using FE grid data of USA. The proposed model provides more accurate results with affordable execution time than other load forecasting models, i.e., mutual information, modified enhanced differential evolution algorithm, and artificial neural network (ANN) based model (MI-mEDE-ANN), accurate fast converging short term load forecasting model (AFC-STLF), Bi-level model, and features selection and ANN-based model (FS-ANN).
Electrical load forecasting is a challenging problem due to random and non-linear behavior of the consumers. With the emergence of the smart grid (SG) and advanced metering infrastructure (AMI), people are capable to record, monitor, and analyze such a complicated non-linear behavior. Electric load forecasting models are indispensable in the decision making, planning, and contract evaluation of the power system. In this regard, various load forecasting models are proposed in the literature, which exhibit trade-off between forecast accuracy and execution time (convergence rate). In this article, a fast and accurate short-term load forecasting model is proposed. The abstractive features from the historical data are extracted using modified mutual information (MMI) technique. The factored conditional restricted boltzmann machine (FCRBM) is empowered via learning to predict the electric load. Eventually, the proposed genetic wind driven optimization (GWDO) algorithm is used to optimize the performance. The remarkable advantages of the proposed framework are the improved forecast accuracy and convergence rate. The forecast accuracy is improved through the use of MMI technique and FCRBM model. On the other side, convergence rate is enhanced by GWDO algorithm. Simulation results illustrate that the proposed fast and accurate model outperforms existing models i.e., Bi-level, MI-artificial neural network (MI-ANN), and accurate fast converging short-term load forecast (AFC-STLF) in terms of forecast accuracy and convergence rate.
In this paper, an efficient model based on factored conditional restricted boltzmann machine (FCRBM) is proposed for electric load forecasting of in smart grid (SG). This FCRBM has deep layers structure and uses rectified linear unit (RELU) function and multivariate autoregressive algorithm for training. The proposed model predicts day ahead and week ahead electric load for decision making of the SG. The proposed model is a hybrid model having four modules i.e., data processing and features selection module, FCRBM based forecaster module, GWDO (genetic wind driven optimization) algorithm-based optimizer module, and utilization module. The proposed model is examined using FE grid data of USA. The proposed model provides more accurate results with affordable execution time than other load forecasting models, i.e., mutual information, modified enhanced differential evolution algorithm, and artificial neural network (ANN) based model (MI-mEDE-ANN), accurate fast converging short term load forecasting model (AFC-STLF), Bi-level model, and features selection and ANN-based model (FS-ANN).
Qazi Zafar Iqbal
added a research item
The smart grid plays a vital role in decreasing electricity cost via Demand Side Management (DSM). Smart homes, being a part of the smart grid, contribute greatly for minimizing electricity consumption cost via scheduling home appliances. However, user waiting time increases due to the scheduling of home appliances. This scheduling problem is the motivation to find an optimal solution that could minimize the Peak to Average Ratio (PAR) and electricity cost with minimum user waiting time. There are many studies on Home Energy Management (HEM) for cost minimization and peak load reduction. However, none of the systems gave sufficient attention to tackle multiple parameters (i.e., electricity cost and peak load reduction) at the same time where user waiting time is considered to be minimum for residential consumers with multiple homes. Hence, in contribution 1, we propose an efficient HEM scheme using the well-known meta-heuristic Genetic Algorithm (GA), the recently developed Cuckoo Search Optimization Algorithm (CSOA) and the Crow Search Algorithm which can be used for electricity cost and peak load alleviation with minimum user waiting time. The integration of a smart electricity storage system is also taken into account for more efficient operation of the HEM System. Furthermore, we took the real-time electricity consumption pattern for every residence, i.e., every home has its own living pattern. The proposed scheme is instigated in a smart building which is comprised of thirty smart homes (apartments). Critical Peak Pricing (CPP) and Real-Time Pricing (RTP) signals are examined in terms of electricity cost assessment for both a single smart home and a smart building. In addition, feasible regions are presented for multiple and single smart homes, which show the relationship among the electricity cost, electricity consumption and user waiting time. Experimental results prove the effectiveness of our proposed scheme for multiple and single smart homes concerning electricity cost and PAR minimization. Moreover, there subsists a tradeoff between electricity cost and user waiting. With the emergence of automated environments, energy demand by consumers is increasing rapidly. More than 80% of total electricity is being consumed in the residential sector. This brings a challenging task of maintaining the balance between demand and generation of electric power. In order to meet such challenges, a traditional grid is renovated by integrating two-way communication between the consumer and generation unit. To reduce electricity cost and peak load demand, DSM is modeled as an optimization problem and the solution is obtained by applying metaheuristic techniques with different pricing schemes. In contribution 2, an optimization technique, the Hybrid Gray Wolf Differential Evolution (HGWDE) is proposed by merging the Enhanced Differential Evolution (EDE) and Gray Wolf Optimization (GWO) schemes using the same RTP and CPP tariffs. Load shifting is performed from on-peak hours to off-peak hours depending on the electricity cost defined by the utility. However, there is a trade-off between User Comfort (UC) and cost. To validate the performance of the proposed algorithm, simulations have been carried out in MATLAB. Results illustrate that using RTP, the PAR is reduced up to 53.02%, 29.02% and 26.55%, while the electricity bill is reduced up to 12.81%, 12.012% and 12.95%, respectively, for 15-min, 30-min and 60-min operational time intervals (OTI). On the other hand, the PAR and electricity bill are reduced up to 47.27%, 22.91%, 22% and 13.04%, 12%, 11.11% using the CPP tariff. Microgrid is a community-based power generation and distribution system that interconnects smart homes with renewable energy sources. Microgrid generates power for electricity consumers and operates in both islanded and grid-connected modes more efficiently and economically. In contribution 3, we propose optimization schemes for reducing electricity cost and minimizing PAR with maximum UC in a smart home. We consider a grid-connected microgrid for electricity generation which consists of wind turbine and photovoltaic (PV) panel. First, the problem was mathematically formulated through Multiple Knapsack (MKP) then it is solved by existing heuristic techniques: GWO, binary particle swarm optimization (BPSO), GA and Wind Driven Optimization (WDO). Furthermore, we also propose three hybrid schemes for electricity cost and PAR reduction: (1) hybrid of GA and WDO named as WDGA; (2) hybrid of WDO and GWO named as WDGWO; and (3) WBPSO, which is the hybrid of BPSO and WDO. In addition, a battery bank system has also integrated to make our proposed schemes more cost-efficient and reliable to ensure stable grid operations. Finally, simulations have been performed to verify our proposed schemes. Results show that our proposed schemes efficiently minimize the electricity cost and PAR. Moreover, our proposed techniques: WDGA, WDGWO and WBPSO outperform the existing heuristic techniques. The advancements in smart grid, both consumers and electricity providing companies can benefit from real-time interaction and pricing methods. In contribution 4, a smart power system is considered, where consumers share a common energy source. Each consumer is equipped with a Home Energy Management Controller (HEMC) as scheduler and a smart meter. The HEMC keeps updating the electricity proving utility with the load profile of the home. The smart meter is connected to power grid having an advanced metering infrastructure which is responsible for two way communication. Genetic teaching-learning based optimization, flower pollination teaching learning based optimization, flower pollination BAT and flower pollination genetic algorithm based energy consumption scheduling algorithms are proposed. These algorithms schedule the loads in order to shave the peak formation without compromising UC. The proposed algorithms achieve optimal energy consumption profile for the home appliances equipped with sensors to maximize the consumer benefits in a fair and efficient manner by exchanging control messages. Control messages contain energy consumption of consumer and RTP information. Simulation results show that proposed algorithms reduce the PAR by 34.56% and help the users to reduce their energy expenses by 42.41% without compromising the comfort. The daily discomfort is reduced by 28.18%.
Qazi Zafar Iqbal
added a research item
With the emergence of the smart grid, both consumers and electricity providing companies can benefit from real-time interaction and pricing methods. In this work, a smart power system is considered, where consumers share a common energy source. Each consumer is equipped with a home energy management controller (HEMC) as scheduler and a smart meter. The HEMC keeps updating the utility with the load profile of the home. The smart meter is connected to a power grid having an advanced metering infrastructure which is responsible for two-way communication. Genetic teaching-learning based optimization, flower pollination teaching learning based optimization, flower pollination BAT and flower pollination genetic algorithm based energy consumption scheduling algorithms are proposed. These algorithms schedule the loads in order to shave the peak formation without compromising user comfort. The proposed algorithms achieve optimal energy consumption profile for the home appliances equipped with sensors to maximize the consumer benefits in a fair and efficient manner by exchanging control messages. Control messages contain energy consumption of consumer and real-time pricing information. Simulation results show that proposed algorithms reduce the peak-to-average ratio by 34.56% and help the users to reduce their energy expenses by 42.41% without compromising the comfort. The daily discomfort is reduced by 28.18%.
Qazi Zafar Iqbal
added a research item
The integration of Smart Grid (SG) with cloud and fog computing has improved the energy management system. The conversion of traditional grid system to SG with cloud environment results in enormous amount of data at the data centers. Rapid increase in the automated environment has increased the demand of cloud computing. Cloud computing provides services at the low cost and with better efficiency. Although problems still exists in cloud computing such as Response Time (RT), Processing Time (PT) and resource management. More users are being attracted towards cloud computing which is resulting in more energy consumption. Fog computing is emerged as an extension of cloud computing and have added more services to the cloud computing like security, latency and load traffic minimization. In this paper a Cuckoo Optimization Algorithm (COA) based load balancing technique is proposed for better management of resources. The COA is used to assign suitable tasks to Virtual Machines (VMs). The algorithm detects under and over utilized VMs and switch off the under-utilized VMs. This process turn down many VMs which puts a big impact on energy consumption. The simulation is done in Cloud Sim environment, it shows that proposed technique has better response time at low cost than other existing load balancing algorithms like Round Robin (RR) and Throttled.
Qazi Zafar Iqbal
added a research item
The integration of Smart Grid (SG) with cloud and fog computing has improved the energy management system. The conversion of traditional grid system to SG with cloud environment results in enormous amount of data at the data centers. Rapid increase in the automated environment has increased the demand of cloud computing. Cloud computing provides services at the low cost and with better efficiency. Although problems still exists in cloud computing such as Response Time (RT), Processing Time (PT) and resource management. More users are being attracted towards cloud computing which is resulting in more energy consumption. Fog computing is emerged as an extension of cloud computing and have added more services to the cloud computing like security , latency and load traffic minimization. In this paper a Cuckoo Optimization Algorithm (COA) based load balancing technique is proposed for better management of resources. The COA is used to assign suitable tasks to Virtual Machines (VMs). The algorithm detects under and over utilized VMs and switch off the under-utilized VMs. This process turn down many VMs which puts a big impact on energy consumption. The simulation is done in Cloud Sim environment, it shows that proposed technique has better response time at low cost than other existing load balancing algorithms like Round Robin (RR) and Throttled.
Qazi Zafar Iqbal
added a research item
With the rapid pace in the evolution and development of technology, the demand of electrical energy is also increasing. Beside the production of energy from traditional and renewable energy sources, the energy management is also required to control the consumption of energy in commercial, industrial and residential houses. Improvement in technologies while reduction in cost has enabled consumers to interconnect the smart devices for reducing cost and energy consumption, this is called internet of things (IoTs). Such increase in the number of smart systems and energy management systems cause a huge amount of data which cannot be processed on traditional system. It requires high computing power and high storage which may be provided by cloud computing. Cloud computing provide resources to customers on demand with low investment and operational cost. The cloud resources are flexible, efficient, scalable and secure. In this paper we simulate the use of cloud computing in smart grid. The datacenters in cloud collect the building’s data, process it and send the results to the building. In this study, we calculate the total response time to each building, the number of requests coming from each building per our, the processing time of each datacenter and the cost of each datacenter (CRRP). The results are useful for energy service providers to select the optimal processing and data storage resources.
Qazi Zafar Iqbal
added 2 research items
Short term load forecasting is indispensable for industrial, commercial, and residential smart grid (SG) applications. In this regard, a large variety of short term load forecasting models have been proposed in literature spaning from legacy time series models to contemporary data analytic models. Some of these models have either better performance in terms of accuracy while others perform well in convergence rate. In this paper, a fast and accurate short term load forecasting framework based on stacked factored conditional restricted boltzmann machine (FCRBM) and conditional restricted boltzmann machine (CRBM) is presented. The stacked FCRBM and CRBM are trained using rectified linear unit (RelU) and sigmoid functions, respectively. The proposed framework is applied to offline demand side load data of US utility. Load forecasts decide weather to increase or decrease the generation of an already running generator or to add extra units or exchange power with neighboring systems. Three performance metrics i.e., mean absolute percentage error (MAPE), normalized root mean square (NRMSE), and correlation coefficient are used to validate the proposed framework. The results show that stacked FCRBM and CRBM are accurate and robust as compared to artificial neural network (ANN) and convolutional neural network (CNN).
Micro-grid (MG) is an emerging component of a smart grid and it is increasing the efficiency and reliability of the power system with the passage of time. MGs often need power in order to fulfill its load requirements, which is transmitted form macro station (MS). Transmission of power from MS cause power line losses. To decrease these power line losses, a hierarchical based coordination (HBC) strategy is proposed for efficiently exchanging the power among MGs. HBC aims to decrease power line losses by making hierarchical coalitions. Results are evaluated and compared with conventional non-coordination model (NCM). This comparison shows the effectiveness of proposed HBC strategy. Results indicate that HBC has decreased the power line losses by 40.1% as compared to conventional NCM.
Qazi Zafar Iqbal
added a research item
With the advent of Smart Grid (SG), it provides the consumers with the opportunity to schedule their power consumption load efficiently in such a way that it reduces their energy cost while also minimizing their Peak to Average Ratio (PAR) in the process. We in this paper target the appliances to schedule in such a way that it increases User Comfort (UC) and decreases electricity consumption load which benefits both consumer and utility. In this paper, we proposed hybrid of Bacterial Forging Algorithm (BFA) and Tabu Search (TS) Algorithm using different Operational time Interval (OTI) to schedule appliances while balancing User Comfort which is the main objective of the Demand Side Management (DSM). This paper tries to reduce both waiting time and electricity cost simultaneously in the new hybrid Bacterial Foraging Tabu Search (BFTS) technique. Real time pricing (RTP) scheme was used to get the total cost of electricity consumed. We compared the results of proposed hybrid scheme with Bacterial Forging (BFA) and Tabu Search (TS) Algorithm using different Operational time Interval (OTI). The result shows effectiveness of using hybrid Bacterial Foraging Tabu Search (BFTS) technique for Demand Side Management (DSM).
Qazi Zafar Iqbal
added a research item
Micro-grid (MG) is an emerging component of a smart grid and it is increasing the efficiency and reliability of the power system with the passage of time. MGs often need power in order to fulfill its load requirements, which is transmitted form macro station (MS). Transmission of power from MS cause power line losses. To decrease these power line losses, a hierarchical based coordination (HBC) strategy is proposed for efficiently exchanging the power among MGs. HBC aims to decrease power line losses by making hierarchical coalitions. Results are evaluated and compared with conventional non-coordination model (NCM). This comparison shows the effectiveness of proposed HBC strategy. Results indicate that HBC has decreased the power line losses by 40.1% as compared to conventional NCM.
Qazi Zafar Iqbal
added 2 research items
Short term load forecasting is indispensable for industrial, commercial, and residential smart grid (SG) applications. In this regard, a large variety of short term load forecasting models have been proposed in literature spaning from legacy time series models to contemporary data analytic models. Some of these models have either better performance in terms of accuracy while others perform well in convergence rate. In this paper, a fast and accurate short term load forecasting framework based on stacked factored conditional restricted boltzmann machine (FCRBM) and conditional restricted boltzmann machine (CRBM) is presented. The stacked FCRBM and CRBM are trained using rectified linear unit (RelU) and sigmoid functions, respectively. The proposed framework is applied to offline demand side load data of US utility. Load forecasts decide weather to increase or decrease the generation of an already running generator or to add extra units or exchange power with neighboring systems. Three performance metrics i.e., mean absolute percentage error (MAPE), normalized root mean square (NRMSE), and correlation coefficient are used to validate the proposed framework. The results show that stacked FCRBM and CRBM are accurate and robust as compared to artificial neural network (ANN) and convolutional neural network (CNN).
With the rapid pace in the evolution and development of technology, the demand of electrical energy is also increasing. Beside the production of energy from traditional and renewable energy sources, the energy management is also required to control the consumption of energy in commercial, industrial and residential houses. Improvement in technologies while reduction in cost has enabled consumers to interconnect the smart devices for reducing cost and energy consumption, this is called internet of things (IoTs). Such increase in the number of smart systems and energy management systems cause a huge amount of data which cannot be processed on traditional system. It requires high computing power and high storage which may be provided by cloud computing. Cloud computing provide resources to customers on demand with low investment and operational cost. The cloud resources are flexible, efficient , scalable and secure. In this paper we simulate the use of cloud computing in smart grid. The datacenters in cloud collect the building's data, process it and send the results to the building. In this study, we calculate the total response time to each building, the number of requests coming from each building per our, the processing time of each datacen-ter and the cost of each datacenter (CRRP). The results are useful for energy service providers to select the optimal processing and data storage resources.
Qazi Zafar Iqbal
added a research item
Microgrid is a community-based power generation and distribution system that interconnects smart homes with renewable energy sources (RESs). Microgrid efficiently and economically generates power for electricity consumers and operates in both islanded and grid-connected modes. In this study, we proposed optimization schemes for reducing electricity cost and minimizing peak to average ratio(PAR) with maximum user comfort (UC) in a smart home. We considered a grid-connected microgrid for electricity generation which consists of wind turbine and photovoltaic (PV) panel. First, the problem was mathematically formulated through multiple knapsack problem (MKP) then solved by existing heuristic techniques: grey wolf optimization (GWO), binary particle swarm optimization (BPSO), genetic algorithm (GA) and wind-driven optimization (WDO). Furthermore, we also proposed three hybrid schemes for electric cost and PAR reduction: (1) hybrid of GA and WDO named WDGA; (2) hybrid ofWDO and GWO named WDGWO; and (3) WBPSO, which is the hybrid of BPSO and WDO. In addition, a battery bank system (BBS) was also integrated to make our proposed schemes more cost-efficient and reliable, and to ensure stable grid operation. Finally, simulations were performed to verify our proposed schemes. Results show that our proposed scheme efficiently minimizes the electricity cost and PAR. Moreover, our proposed techniques, WDGA, WDGWO and WBPSO, outperform the existing heuristic techniques.
Qazi Zafar Iqbal
added a research item
In this paper, we propose a home energy management (HEM) scheme in the residential area for electricity cost and peak to average ratio (PAR) reduction. Furthermore, reduction in imported electricity from the external grid is also the objective of this study. Our proposed scheme schedules smart appliances as well as electrical vehicles (EVs) charging/discharging optimally according to the consumer preferences. Each consumer has its own grid-connected microgrid for electricity generation; which consists of wind turbine, solar panel, micro gas turbine (MGT) and energy storage system (ESS). Furthermore, the scheduling problem is mathematically formulated and solved by mixed integer linear programming (MILP). We also provide the comparison of the optimal solutions, while considering EVs with and without discharging capabilities. Findings from simulations affirm our proposed scheme in terms of above-mentioned objectives. Index Terms-Demand side management; home energy management ; mixed integer linear programming
Qazi Zafar Iqbal
added a research item
Smart Grid (SG) plays vital role to utilize electric power with high optimization through Demand Side Management (DSM). Demand Response (DR) is a key program of DSM which assist SG for optimization. Smart Home (SH) is equipped with smart appliances and communicate bidirectional with SG using Smart Meter (SM). Usually, appliances considered as working for specific time-slot and scheduler schedule them according to tariff. If actual run and power consumption of appliances are observed closely, appliances may run in phases, major tasks, sub-tasks and run continuously. In the paper, these phases have been considered to schedule the appliances using three optimization algorithms. In one way, appliances were scheduled to reduce the cost considering continuous run for given time slot according to their power load given by company’s manual. In other way, actual running of appliances with major and sub-tasks were paternalized and observed the actual consumption of load by the appliances to evaluate true cost. Simulation showed, Binary Particle Swarm Optimization (BPSO) scheduled more optimizing scheduling compared to Fire Fly Algorithm (FA) and Bacterial Frogging Algorithm (BFA). A hybrid technique of FA and GA have also been proposed. Simulation results showed that the technique performed better than GA and FA.
Qazi Zafar Iqbal
added a research item
With the emergence of automated environments, energy demand by consumers is increasing rapidly. More than 80% of total electricity is being consumed in the residential sector. This brings a challenging task of maintaining the balance between demand and generation of electric power. In order to meet such challenges, a traditional grid is renovated by integrating two-way communication between the consumer and generation unit. To reduce electricity cost and peak load demand, demand side management (DSM) is modeled as an optimization problem, and the solution is obtained by applying meta-heuristic techniques with different pricing schemes. In this paper, an optimization technique, the hybrid gray wolf differential evolution (HGWDE), is proposed by merging enhanced differential evolution (EDE) and gray wolf optimization (GWO) scheme using real-time pricing (RTP) and critical peak pricing (CPP). Load shifting is performed from on-peak hours to off-peak hours depending on the electricity cost defined by the utility. However, there is a trade-off between user comfort and cost. To validate the performance of the proposed algorithm, simulations have been carried out in MATLAB. Results illustrate that using RTP, the peak to average ratio (PAR) is reduced to 53.02%, 29.02% and 26.55%, while the electricity bill is reduced to 12.81%, 12.012% and 12.95%, respectively, for the 15-, 30- and 60-min operational time interval (OTI). On the other hand, the PAR and electricity bill are reduced to 47.27%, 22.91%, 22% and 13.04%, 12%, 11.11% using the CPP tariff.
Qazi Zafar Iqbal
added an update
Nothing in the world can take the place of persistence. Talent will not; nothing is more common than unsuccessful men with talent. Genius will not; unrewarded genius is almost a proverb. Education will not; the world is full of educated derelicts. Persistence and determination alone are omnipotent. The slogan, 'Press on,' has solved and always will solve the problems of the human race
--Calvin Coolidge
 
Qazi Zafar Iqbal
added a research item
Smart Grid (SG) plays vital role to utilize electric power with high optimization through Demand Side Management (DSM). Demand Response (DR) is a key program of DSM which assist SG for optimization. Smart Home (SH) is equipped with smart appliances and communicate bidirectional with SG using Smart Meter (SM). Usually, appliances considered as working for specific time-slot and scheduler schedule them according to tariff. If actual run and power consumption of appliances are observed closely, appliances may run in phases, major tasks, sub-tasks and run continuously. In the paper, these phases have been considered to schedule the appliances using three optimization algorithms. In one way, appliances were scheduled to reduce the cost considering continuous run for given time slot according to their power load given by companys manual. In other way, actual running of appliances with major and sub-tasks were paternalized and observed the actual consumption of load by the appliances to evaluate true cost. Simulation showed, Binary Particle Swarm Optimization (BPSO) scheduled more optimizing scheduling compared to Fire Fly Algorithm (FA) and Bacterial Frogging Algorithm (BFA). A hybrid technique of FA and GA have also been proposed. Simulation results showed that the technique performed better than GA and FA.
Qazi Zafar Iqbal
added an update
Hello Zafar Iqbal,
We are urgently seeking the following expert to join a multidisciplinary team working on the challenge described below:
Linux programmer/coder, preferably with package manager knowledge.  Experience in translating Excel files into another markup language is an asset.
*This is not a competition, and only a single team will be working on this challenge, with regular meetings with the Seeker.*
If you are accepted into the team and your team’s solution is fully accepted and awarded for both phases of this project, and all IP is transferred, your team will be paid a total of $25,000.00 to be split equally between team members.
Following is a summary of the challenge, more information will be provided to selected team members:
Translating Complex Excel Logic into Interactive Visualizations -------------------------------- To meet the increasing global demand for food, new products for crop protection are essential. All new biologically active ingredients go through rigorous, costly and time-consuming evaluations by developers and regulatory agencies before commercialization. Recognizing that a picture is worth a thousand words, the Seeker wants to 'see' a specific decision-making regulatory model to understand the decision logic, extract insights, and proactively assess potential decisions. Specifically, the Seeker needs to solve a challenging puzzle - how to decipher, visualize, and interact with the decision logic currently codified in an extremely complex, interoperable Excel spreadsheet with over 12 sheets all containing ~1000 cells interlinked to cells in the same or other sheets with logic containing variations of IF, MATCH, INDEX and other Excel functions. It is likely non-trivial to deconvolute this spreadsheet logic via manual methods. Solving this thought-provoking programming and user interface challenge requires a special collaborative effort applying expertise in visualization, programming and toxicology. The goals are to develop Linux-compatible software that can accurately decode, translate and visualize the logic hierarchy of the spreadsheet, and to create a bespoke interactive user interface/experience to explore and visually represent different data inputs and decision scenarios using the logic.
A single multidisciplinary team will be chosen and will check-in at key points with the Seeker during solution development. This challenge will be conducted in two phases.
Please note that it is possible that the Seeker will make a go/no go decision for Phase 2 after evaluation of Phase 1 deliverables and some team members may be changed at the discretion of IdeaConnection after Phase 1 based on the capabilities required for each phase.
Phase 1 - Write software to decode the Excel spreadsheet, visualize, and create a web interface 1.      Recommend open source visualization software to represent and display the logic model from the Excel spreadsheet; 2.      Develop software to decode (analyze, understand, and translate) the decision-making logic from different versions of an Excel spreadsheet into an open source mark-up language compatible with the visualization software, ensuring that there is flexibility to enable corrections and revisions to the logic rules, and future modifications to incorporate entire databases of data and decisions and extend analytical capabilities; 3.      Create a web-based application interface with the open source visualization software that duplicates the functionality of the Excel spreadsheet enables users to interact with the logic model, test input variables to see the decision path, and view the logic output; 4.      Validate the logic model using input data and decisions provided by the Seeker; 5.      Document differences between the logic model decoded from two spreadsheet versions and other insights on the decision logic; and, 6.      Provide the code and documentation for the logic translation process and application.
Phase 2 - Design and develop a user interface/experience for the decision logic model 1.      Develop and refine use cases with the Seeker; 2.      Propose a design for an interactive, web-based UI/UX with the decision logic model that will enable:   2.1.  The user to explore the impact of input changes, generate and save annotated representations of different assessment scenarios from the decoded spreadsheet logic; and,   2.2.  Additional, future functionality to permit the user to overlay and query entire databases. 3.      Develop the UI/UX software; 4.      Provide the code and documentation for UI/UX implementation; and, 5.      Provide documentation for user and administrator guidance.
**Phase 1 must be completed prior to March 1, 2018
*Award Details:* If your team's solution to this challenge is accepted in full and awarded for Phase 1, $12,500.00 USD paid to the team to be split equally among team members if the solution is accepted and fully awarded. An additional $12,500.00 USD paid to the team to be split equally among team members if the solution is accepted and fully awarded for Phase 2.
If you are accepted to work with the team, you will be working online with approximately 3-4 other people including one experienced Facilitator.
If you want to work on this challenge, please click the link below to confirm that you are available to focus your mind on this problem, part time, over the next approximately 80 days and that you will be available for at least 1 or 2 online meetings each week:
Please do not apply if you cannot commit this time to working with the team.
*Important*: If shortlisted, you will be required to sign a challenge agreement within 24 hours.  If you are currently employed and your team's solution is accepted, *you will be required to get an IP release signed by your employer*.   Do not apply if you are not certain that your employer will sign this release.
REFER A FRIEND to this challenge and earn $500: https://www.ideaconnection.com/refer-a-colleague.html
We look forward to your interest and are excited to have you working with us.
Sincerely, The IdeaConnection Team
 
Qazi Zafar Iqbal
added an update
PhD students, Post-doc researchers and academic staff vacancy
Currently, we would like to have one or two post-doc researcher and assisent professor or associate professor in our research group.
 
Qazi Zafar Iqbal
added a research item
The smart grid plays a vital role in decreasing electricity cost through Demand Side Management (DSM). Smart homes, a part of the smart grid, contribute greatly to minimizing electricity consumption cost via scheduling home appliances. However, user waiting time increases due to the scheduling of home appliances. This scheduling problem is the motivation to find an optimal solution that could minimize the electricity cost and Peak to Average Ratio (PAR) with minimum user waiting time. There are many studies on Home Energy Management (HEM) for cost minimization and peak load reduction. However, none of the systems gave sufficient attention to tackle multiple parameters (i.e., electricity cost and peak load reduction) at the same time as user waiting time was minimum for residential consumers with multiple homes. Hence, in this work, we propose an efficient HEM scheme using the well-known meta-heuristic Genetic Algorithm (GA), the recently developed Cuckoo Search Optimization Algorithm (CSOA) and the Crow Search Algorithm (CSA), which can be used for electricity cost and peak load alleviation with minimum user waiting time. The integration of a smart Electricity Storage System (ESS) is also taken into account for more efficient operation of the Home Energy Management System (HEMS). Furthermore, we took the real-time electricity consumption pattern for every residence, i.e., every home has its own living pattern. The proposed scheme is implemented in a smart building; comprised of thirty smart homes (apartments), Real-Time Pricing (RTP) and Critical Peak Pricing (CPP) signals are examined in terms of electricity cost estimation for both a single smart home and a smart building. In addition, feasible regions are presented for single and multiple smart homes, which show the relationship among the electricity cost, electricity consumption and user waiting time. Experimental results demonstrate the effectiveness of our proposed scheme for single and multiple smart homes in terms of electricity cost and PAR minimization. Moreover, there exists a tradeoff between electricity cost and user waiting.
Qazi Zafar Iqbal
added a research item
In the smart grid (SG) users in residential sector adopt various load scheduling methods to manage their consumption behavior with specific objectives. In this paper, we focus on the problem of load scheduling under utility and rooftop photovoltaic (PV) units. We adopt genetic algorithm (GA), binary particle swarm optimization (BPSO), wind driven optimization (WDO), and proposed genetic wind driven optimization (GWDO) algorithm to schedule the operation of interruptible appliances (IA) and non interruptible appliances (Non-IA) in order to reduce electricity cost and peak to average ratio (PAR). For energy pricing combined real time pricing (RTP) and inclined block rate (IBR) is used because in case of only RTP their is possibility of building peaks during off peak hours that may damage the entire power system. The proposed algorithm shift load from peak consumption hours to off peak hours and to hours with high generation from rooftop PV units. For practical consideration, we also take into consideration pricing scheme, rooftop PV units, and ESS in our system model, and analyze their impacts on electricity cost and PAR. Simulation results show that our proposed scheduling algorithm can affectively reflect and affect users consumption behavior and achieve the optimal electricity cost and PAR.
Qazi Zafar Iqbal
added a research item
Renewable energy sources (RESs) are considered as future replacement of traditional energy generation sources with zero carbon emission and low price electricity producers. RESs are intermittent, uncertain and random in nature, they do not produce fixed amount of energy and heavily depend upon weather, season and area. In this paper, new trends in the integration of photovoltaic and wind turbine are presented. This paper discusses the integration of RESs at three level i.e. consumer level, micro grid level and main grid level. A comprehensive review of the intermittent and stochastic nature of RESs is also provided. Additionally, fault protection concerns and the feasibility of RESs are discussed. Moreover, the usage of storage system to deal with the fluctuating behavior of RESs is presented.
Qazi Zafar Iqbal
added an update
Hafiz Majid Hussain
added 3 research items
Traditional power grid and its demand-side management (DSM) techniques are centralized and mainly focus on industrial consumers. The ignorance of residential and commercial sectors in DSM activities degrades the overall performance of a conventional grid. Therefore, the concept of DSM and demand response (DR) via residential sector makes the smart grid (SG) superior over the traditional grid. In this context, this paper proposes an optimized home energy management system (OHEMS) that not only facilitates the integration of renewable energy source (RES) and energy storage system (ESS) but also incorporates the residential sector into DSM activities. The proposed OHEMS minimizes the electricity bill by scheduling the household appliances and ESS in response to the dynamic pricing of electricity market. First, the constrained optimization problem is mathematically formulated by using multiple knapsack problems, and then solved by using the heuristic algorithms; genetic algorithm (GA), binary particle swarm optimization (BPSO), wind driven optimization (WDO), bacterial foraging optimization (BFO) and hybrid GA-PSO (HGPO) algorithms. The performance of the proposed scheme and heuristic algorithms is evaluated via MATLAB simulations. Results illustrate that the integration of RES and ESS reduces the electricity bill and peak-to-average ratio (PAR) by 19.94% and 21.55% respectively. Moreover, the HGPO algorithm based home energy management system outperforms the other heuristic algorithms, and further reduces the bill by 25.12% and PAR by 24.88%.
The performance and comparative analysis of home energy management controller using three optimization techniques; genetic algorithm (GA), enhanced differential evolution (EDE) and optimal stopping rule (OSR) has been evaluated in this paper. In this regard, a generic system model consisting of home area network, advanced metering infrastructure, home energy management controller, and smart appliances has been proposed. Price threshold policy and priority of appliance have also been considered to depict monthly and yearly average electricity bill savings and appliance delay using day-ahead real-time pricing (DA-RTP). Simulation results validate that all our proposed schemes successfully shifts the appliance operations to off-peak times and results in reduced electricity bill with reasonable waiting time.
Smart grid (SG) is one of the most advanced technologies, which plays a key role in maintaining balance between demand and supply by implementing demand response (DR). In SG the main focus of the researchers is on home energy management (HEM) system, that is also called demand side management (DSM). DSM includes all responses, which adjust the consumerâ ˘ A ´ Zs electricity consumption pattern, and make it match with the supply. If the main grid cannot provide the users with sufficient energy, then the smart scheduler (SS) integrates renewable energy source (RES) with the HEM system. This alters the peak formation as well as minimizes the cost. Residential users basically effect the overall performance of traditional grid due to maximum requirement of their energy demand. HEM benefits the end users by monitoring, managing and controlling their energy consumption. Appliance scheduling is integral part of HEM system as it manages energy demand according to supply, by automatically controlling the appliances or shifting the load from peak to off peak hours. Recently different techniques based on artificial intelligence (AI) are being used to meet aforementioned objectives. In this paper, three different types of heuristic algorithms are evaluated on the basis of their performance against cost saving, user comfort and peak to average ratio (PAR) reduction. Two techniques are already existing heuristic techniques i.e. harmony search(HS) algorithm and enhanced differential evolution (EDE) algorithm. On the basis of aforementioned two algorithms a hybrid approach is developed i.e. harmony search differential evolution (HSDE). We have done our problem formulation through multiple knapsack problem (MKP), that the maximum consumption of electricity of consumer must be in the range which is bearable for utility and also for consumer in sense of electricity bill. Finally simulation of the proposed techniques will be conducted in MATLAB to validate the performance of proposed scheduling
Private Profile
added a research item
Controlling power utilization in the residential area is one of the major challenges in the smart grid (SG). Demand response (DR) has played a vital role in energy management and improved it with the involvement of residential consumers who participate in such programs from utilities for scheduling their appliances to the off peak hours. In this paper, we have proposed a worldwide adaptive thermostat model for effectively managing the power in all countries of the world. The proposed approach has been evaluated with the help of fuzzy logic and its two inference systems (FIS): 1) Mamdani and 2) Takagi Sugeno. Utilizing the membership functions; outdoor temperature, user occupancy, utility price and initialized setpoints are evaluated for maintaining the buildings temperature. Furthermore, energy consumption in buildings is analyzed by tuning the indoor initialized setpoints while considering all the aforementioned parameters. Simulations are conducted in Matlab to validate the proposed system model and results show that energy consumption in cold countries is reduced upto 45% as compared to the existing programmable approach. Index Terms—Energy management, thermostat, smart grid, fuzzy logic, takagi sugeno fuzzy inference system, mamdani fuzzy inference system
Qazi Zafar Iqbal
added an update
mmmmmmm
 
Private Profile
added a research item
Electricity is a controllable and convenient form of energy. In this paper we discus about the electricity control. In current years Demand Side Management (DSM) techniques are designed. For residential and commercial sectors. These techniques are very effective to control the load profile of customer in grid area network. In this paper we use two optimization techniques: Harmony Search Algorithm (HSA) and Firefly Algorithm (FA).In our work we categorize smart appliances in three different categories on the basis of their energy consumption. For energy pricing we use Time of Use (ToU)pricing signal.Simulation result verify our adopted approach significantly reduce the cost without compromise the user comfort.
Private Profile
added 2 research items
With the emergence of smart grid (SG), the residents have the opportunity to integrate renewable energy sources (RESs) and take part in demand side management (DSM). In this regard, we design energy management control unit (EMCU) based on genetic algorithm (GA), binary particle swarm optimization (BPSO), and wind driven optimization (WDO) to schedule appliances in presence of objective function, constraints, control parameters, and comparatively evaluate the performance. For energy pricing, real time pricing (RTP) plus inclined block rate (IBR) is used. RESs integration to SG is a challenge due stochastic nature of RE. In this paper, two techniques are addressed to handle the stochastic nature of RE. First one is energy storage system (ESS) which smooths out variation in RE generation. Second one is the trading/cooperation of excess generation to neighboring consumers. The simulation results show that WDO perform more efficiently than unscheduled in terms of reduction in: electricity cost, the tradeoff between electricity cost and waiting time, and peak to average ratio (PAR). Moreover, incorporation of RESs into SG design increase the revenue and reduce carbon emission.
In this paper, an energy management controller (EMC) is designed using three optimization techniques: harmony search algorithm (HSA), firefly algorithm (FA) and enhanced differential evolution (EDE). The objectives of this work are to minimize electricity cost as well as peak to average ratio (PAR) while maintaining the user comfort (UC). Critical peak pricing (CPP) is used for the calculation of electricity bill. The trade-off between UC and electricity cost is exploited in such a way that a stability is achieved among UC and electricity price that is preferred by the consumer. Reduction in PAR is beneficial for both consumer and utility as it provides stability to the electric grid.
Private Profile
added 2 research items
In this paper performance of Home Energy Management System (HEMS) is evaluated using two meta-heuristic techniques: Harmony Search Algorithm (HSA) and BAT Algorithm. Appliances are classified into three categories according to their characteristics. Critical peak pricing is used for electricity price calculation as electricity pricing scheme. The main purpose is electricity cost reduction, electricity consumption, peak to average ratio reduction and maximizing User Comfort (UC) by reducing waiting time. Simulation results show the overall effectiveness of HSA.
Proliferation in smart grid gave rise to different Demand Side Management (DSM) techniques, designed for type of sectors i.e. domestic, trade and commercial sectors, very effective in smoothening load profile of the consumers in grid area network. To resolve energy crises in residential areas, smart homes are introduced; contains Smart Meters, allows bidirectional communication between utilities and customers. For this purpose, different heuristic techniques are approached to overcome state of the art energy crisis which provide best optimal solution. The purpose of our implementation is to reduce the total cost and Peak to Average Ratio value while keeping in mind that there is a trade-off of these with waiting time up to an acceptable limit. Our proposed scheme uses heuristic technique Harmony Search Algorithm with Fish Swarm Algorithm to achieve the defined goals. Real time prizing signal is used for bill calculation in Advanced Metering Infrastructure.
Private Profile
added 31 research items
In smart grid, several optimization techniques are developed for residential load scheduling purpose. Preliminary all the conventional techniques aimed at minimizing the electricity consumption cost. This paper mainly focuses on minimization of electricity cost and maximiza-tion of user comfort along with the reduction of peak power consumption. We develop a multi-residential load scheduling algorithm based on two heuristic optimization techniques: genetic algorithm and binary particle swarm optimization. The day-ahead pricing mechanism is used for this scheduling problem. The simulation results validate that the proposed model has achieved substantial savings in electricity bills with maximum user comfort. Moreover, results also show the reduction in peak power consumption. We analyzed that user comfort has significant effect on electricity consumption cost.
Nowadays, Energy become the most valued necessity. Energy crisis becomes a critical issue of this era. Energy demand is increasing day by day, due to which peak load creation occurs. In order to handle the critical situation of the energy crisis, many techniques and methods are implemented. This can be done by replacing the traditional grid with smart grid and scheduling of appliances at Demand Side Management (DSM). Our main focus is on load management and minimization of cost which can be done by load shifting from on peak hours to off peak hours. We have achieved objectives by using two meta-heuristic optimization techniques; Harmony Search Algorithm (HSA) and EarthWorm optimization Algorithm (EWA). Simulation results show that the approaches we adopted reduce the cost, reduce the Peak Average Ratio (PAR) by load shifting from on peak to off peak hours between the min and max interval with a low difference.
In the past few years, a number of optimization techniques have been designed for Home Energy Management System (HEMS). In this paper, we evaluated the performance of two heuristic algorithms, i.e., Harmony Search Algorithm (HSA) and Tabu Search (TS) for optimization in residential area. These algorithms are used for efficient scheduling of Smart Appliances (SA) in Smart Homes (SH). Evaluated results show that TS performed better than HSA in achieving our defined goals of cost reduction, improving User Comfort (UC) level and minimization of Peak to Average Ratio (PAR). However, there remains a trade-off between electricity cost and waiting time.
Qazi Zafar Iqbal
added a research item
With the emergence of smart grid (SG), the residents have the opportunity to integrate renewable energy sources (RESs) and take part in demand side management (DSM). In this regard, we design energy management control unit (EMCU) based on genetic algorithm (GA), binary particle swarm optimization (BPSO), and wind driven optimization (WDO) to schedule appliances in presence of objective function, constraints, control parameters, and comparatively evaluate the performance. For energy pricing, real time pricing (RTP) plus inclined block rate (IBR) is used. RESs integration to SG is a challenge due stochastic nature of RE. In this paper, two techniques are addressed to handle the stochastic nature of RE. First one is energy storage system (ESS) which smooths out variation in RE generation. Second one is the trading/cooperation of excess generation to neighboring consumers. The simulation results show that WDO perform more efficiently than unscheduled in terms of reduction in: electricity cost, the tradeoff between electricity cost and waiting time, and peak to average ratio (PAR). Moreover, incorporation of RESs into SG design increase the revenue and reduce carbon emission.
Private Profile
added 4 research items
Today’s buildings are responsible for about 40% of total energy consumption and 30–40% of carbon emissions, which are key concerns for the sustainable development of any society. The excessive usage of grid energy raises sustainability issues in the face of global changes, such as climate change, population, economic growths, etc. Traditionally, the power systems that deliver this commodity are fuel operated and lead towards high carbon emissions and global warming. To overcome these issues, the recent concept of the nearly zero energy building (nZEB) has attracted numerous researchers and industry for the construction and management of the new generation buildings. In this regard, this paper proposes various demand side management (DSM) programs using the genetic algorithm (GA), teaching learning-based optimization (TLBO), the enhanced differential evolution (EDE) algorithm and the proposed enhanced differential teaching learning algorithm (EDTLA) to manage energy and comfort, while taking the human preferences into consideration. Power consumption patterns of shiftable home appliances are modified in response to the real-time price signal in order to get monetary benefits. To further improve the cost and user discomfort objectives along with reduced carbon emission, renewable energy sources (RESs) are also integrated into the microgrid (MG). The proposed model is implemented in a smart residential complex of multiple homes under a real-time pricing environment. We figure out two feasible regions: one for electricity cost and the other for user discomfort. The proposed model aims to deal with the stochastic nature of RESs while introducing the battery storage system (BSS). The main objectives of this paper include: (1) integration of RESs; (2) minimization of the electricity bill (cost) and discomfort; and (3) minimizing the peak to average ratio (PAR) and carbon emission. Additionally, we also analyze the tradeoff between two conflicting objectives, like electricity cost and user discomfort. Simulation results validate both the implemented and proposed techniques.
Smart grid is envisioned to meet the 21st century energy requirements in a sophisticated manner with real time approach by integrating the latest digital communications and advanced control technologies to the existing power grid. It will dynamically connect all the stake holders of smart grid through enhanced energy efficiency awareness corridor. Smart Homes (SHs), Home Energy Management Systems (HEMS) and effect of home appli- ances scheduling in smart grid are now familiar research topics in electrical engineering. Peak load management and reduction of Peak to Average Ratio (PAR) and associated methods are under focus of researchers since decades. These topics have got new dimensions in smart grid environment. This dissertation aims at simulation study for effective Demand Side Management (DSM) in smart grid environment. This work is mainly focused on optimal load scheduling for energy cost minimization and peak load reduction. This work comprehensively reviews the smart grid applications, communication technologies, load management techniques, pricing schemes and related topics in order to provide an insight to the environment required for dynamic DSM. Various network attributes such as Internet Pro- tocol (IP) support, power usage, data rate etc. are considered to compare the communications technologies in smart grid context. Techniques suitable for Home Area Networks (HANs) such as ZigBee, Bluetooth, Wi-Fi, 6LoWPAN and Z-wave are discussed and compared in context of consumer concerns and network attributes. A similar approach in context of utilities’ concerns is adopted for wireless communications techniques for Neighborhood Area Networks (NANs), which include WiMAX and GSM based cellular standards. Issues and challenges regarding dynamic DSM in smart grid have been discussed briefly. DSM is supposed to have a vital role in future energy management systems and is one of the hot research areas. This study presents detailed review and analytical comparison of DSM tech- niques along with related technologies and implementation challenges in smart grid. It also covers consumers and utilities concerns in context of DSM to enhance the readers’ intuition about the topic. Two major types of DSM schemes, incentive based and dynamic pricing based, have been discussed and compared analytically. Dynamic pricing based HEMS are emphasized as important tools for peak load reduction and consumers’ energy cost minimization. Dynamic pricing based HEMS and their associated optimization techniques along with analytical comparison of the latest schemes have been described. Comparison of DSM techniques and study of latest HEMS scheme provided the base for new ideas of partial baseline load and reserved interrupting load to formulate two unique energy cost minimization problems. These models resulted the following two solutions in which scheduling has been carried out through many different algorithms to reduce peak load and consequently the PAR. This work includes novel appliance scheduling solution named; Comprehensive Home Energy Management Architecture (CHEMA), with multiple integrated scheduling options in smart grid environment. Multiple layers of enhanced architecture are modeled in Simulink with embed- ded MATLAB code. Single Knapsack is used for scheduling and four different cases for cost reduction are modeled. Fault identification and electricity theft control have also been added along with the carbon foot prints reduction for environmental concerns. Simulation results have shown the peak load reduction of 22.9% for unscheduled load with Persons Presence Controller (PPC), 23.15% for scheduled load with PPC and 25.56% for flexible load scheduling. Simi- larly total cost reduction of 23.11%, 24% and 25.7% has been observed, respectively. Smart grid interface layer and load forecasting layers are not implemented in current work and will be focused in future work. Another novel comparative approach has also been proposed in this research, which investi- gates the effect of multiple pricing schemes and optimization techniques for cost minimization and peak load reduction. The proposed model uses multiple pricing schemes including Time of Use (ToU), Real Time Pricing (RTP) day ahead case and Critical Peak Pricing (CPP). Pro- posed optimization problem has been solved with multiple optimization techniques including Knapsack, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). Knapsack is used with two options of limited slots scheduling and whole day scheduling. Comparative results of the multiple pricing and optimization schemes have been discussed. Results show that the best combination achieved with GA and CPP with 39.9223% cost reduction. PSO showed the 43.73% cost reduction with all the pricing schemes. The proposed schemes have many applications for peak load reduction and energy cost mini- mization to benefit consumers and utilities. A user can schedule his load using one of the op- tions provided in CHEMA according to his preferences. Similarly, maintenance activities can be accommodated without disturbing the pre-defined schedule by using reserved interrupting slots. In large buildings, reserved slots can be used to schedule heavy loads without generating a peak.
The smart grid appears an advanced and upgraded form of the power grid. As an essential component of the smart grid, demand side management (DSM) enhances the energy efficiency of electricity infrastructure. In this thesis, we propose home energy management controller (HEMC) based on heuristic algorithms to reduce electricity expense, peak to average ratio (PAR), and maximize user comfort. We consider proposed HEMC for a single home and multiple homes. In particular, for multiple homes we classify modes of operation for the appliances according to their energy consumption with varying operation time slots. This strategy influences the consumers to reshape energy consumption profile in response to electricity cost. In order to achieve an optimal scheduling of energy consumption profile of the household appliances, we explore heuristic algorithms, such as wind-driven optimization (WDO), harmony search algorithm (HSA), and genetic algorithm (GA). We also propose a hybrid optimization algorithm genetic harmony search algorithm (GHSA) that can schedule energy consumption profile in an appropriate way. The existing and proposed optimization algorithms are investigated by considering single home and multiple homes with real-time electricity pricing (RTEP) and critical peak pricing (CPP) tariffs. Finally, simulation results are conducted which shows proposed algorithm GHSA performs efficiently to reduce electricity cost, PAR, and maximize user comfort.
Private Profile
added 8 research items
In smart grid, several optimization techniques are developed for residential load scheduling purpose. Most of these conventional techniques of demand side management aim at minimizing the energy consumption cost. Maintaining a balance between two conflicting objectives: energy consumption cost and user comfort is still a challenging task to achieve. Therefore, in this paper, we focus on minimization of electricity cost and user discomfort while taking into account the peak energy consumption. In this regard, we implement and analyze the performance of a traditional technique; dynamic programming (DP) and two heuristic optimization techniques: genetic algorithm (GA) and binary particle swarm optimization (BPSO) for residential load. Based on these techniques, we propose a hybrid scheme; GAPSO for residential load scheduling, so as to optimize the desired objective function. In order to alleviate the complexity of the problem, the multi-dimensional knapsack is used to formulate the energy scheduling problem. The proposed model is evaluated based on two pricing schemes: day-ahead and critical peak pricing for single and multiple days. Furthermore, feasible regions are calculated and analyzed to develop a relationship between power consumption, electricity cost, and user discomfort. The simulation results are compared with DP, and validate that the proposed model along with the proposed hybrid scheme reflects substantial savings in electricity bills with minimum user discomfort. Moreover, results also show a phenomenal reduction in peak power consumption.
With the advent of smart grid and demand side management techniques, users have opportunity to reduce their electricity cost without compromising their comfort. In this thesis, we evaluate the performance of home energy management system based on user satisfaction using evolutionary computation. Our objective is to maximize the total user satisfaction within user defined budget. For the budget, three different scenarios are taken into account: 0.25/day, $0.50/day and $1.00/day. Problem formulation is performed using multiple knapsack problem. Feasible regions for three scenarios are also calculated. To obtain the desired satisfaction, three optimization techniques are used: genetic algorithm, enhanced differential evolution algorithm, and harmony search algorithm. The proposed techniques are evaluated and their simulation results are compared in terms of achieved satisfaction.
With the emergence of the smart grid (SG), the residents have the opportunity to integrate renewable energy sources (RESs) and take part in demand side management (DSM). In this thesis, we introduce generic home energy management control system (HEMCS) model having energy management control unit (EMCU) to efficiently schedule household load and integrate RESs. The EMCU based on genetic algorithm (GA), binary particle swarm optimization (BPSO), wind driven optimization (WDO), and our proposed genetic wind driven optimization (GWDO) algorithm to schedule appliances of single home and multiple homes. For energy pricing, combined real time pricing (RTP) and inclined block rate (IBR) is adopted, because in case of only RTP there is a possibility of building peaks during off peak hours that may damage the entire power system. Moreover, to control demand under the capacity of electricity grid station feasible region is defined and problem is formulated using multiple knapsack. Energy efficient integration of RESs in SG is a challenge due to time varying and intermittent nature of RE. In this thesis, two techniques are used to handle time varying and intermittent nature of RE. First one is energy storage system (ESS) that smooth out variations in RE generation. Second is trading of the surplus generation among neighboring consumers. The simulation results show that our proposed scheme can mitigate voltage rise problem in areas with high penetration of RESs and reduce electricity cost and peak to average ratio (PAR) of aggregated load.
Qazi Zafar Iqbal
added a research item
Recently, Home Energy Management (HEM) controllers have been widely used for residential load management in a smart grid. Generally, residential load management aims {to reduce the electricity bills and also curtail the Peak-to-Average Ratio (PAR)}. In this paper, we design a HEM controller on the {basis} of four heuristic algorithms: Bacterial Foraging Optimization Algorithm (BFOA), Genetic Algorithm (GA), Binary Particle Swarm Optimization (BPSO), and Wind Driven Optimization (WDO). Moreover, we proposed {a} hybrid algorithm which is Genetic BPSO (GBPSO). All the selected algorithms are tested with the consideration of essential home appliances in Real Time Pricing (RTP) environment. Simulation results show that each algorithm in the HEM controller reduces the electricity cost and curtails the PAR. GA based HEM controller performs relatively better in term of PAR reduction; it curtails approximately $34\%$ PAR. Similarly, BPSO based HEM controller performs relatively better in term of cost reduction {, as} it reduces approximately $36\%$ cost. Moreover, GBPSO based HEM controller performs better than the other algorithms based HEM controllers in terms of both cost reduction and PAR curtailment.
Qazi Zafar Iqbal
added 4 research items
In this paper, we propose a novel strategy for a Demand Side Management (DSM) in a Smart Grid (SG). In this strategy, three types of loads are considered, i.e., residential load, commercial load and industrial load. The larger number of appliances of different power rating for each type of load is considered in this work. The focus of this work is to minimize the Peak to Average Ratio (PAR) to increase the efficiency of SG, by increasing the utilization of spinning reserves. On the other hand, our aim is to minimize the electricity consumption cost. Tackling the large number of appliances in an SG is a challenging task, because it increases the complexity of the problem. However, in literature the focus is on small number of appliance. In this work, the load scheduling problem is mathematically formulated and solved by using genetic algorithm. The simulation results show that the propose algorithm reduces the cost, while reducing the peak load demand of the SG.
Demand Side Management (DSM) mechanism is used for the implementation of different strategies to encourage residential users to reduce electricity bill as well as energy demand. There is also a close relationship between the consumer and utility for equally benefiting to both in terms of grid stability and bill reduction. Extensive research is undertaken now a days in order to make practical implementation on the possible use of different DSM strategies to regulate the energy demand and carbon emission reduction in the World. The major objective of this work is to study the DSM-based approaches which could be helpful in achieving significant electricity demand reduction at the electricity distribution network which is directly connected to the commercial and residential sector especially. In this work, we use an optimization algorithm to obtain the optimal solution for residential electricity load management in a typical household setting. There are two major tasks of this algorithms; firstly, electricity bill minimization of residential user in time of use pricing models, secondly, peaks reduction of demand curve (peak shaving) which will eventually minimize the investment cost of utility including, peak power plants, and transmission lines. Three types of smart appliances are considered; without delay, delay of one hour, delay of five hours. To validate the effectiveness of the proposed algorithm, mathematical models of appliances based on their length of operation time is developed.
Efficient energy management requires smart approaches in demand side as well as demand response management assisted by smart, innovative, and computationally feasible schemes. Artificial intelligence algorithms are increasingly becoming helpful in generating multiple scenarios for a range of real world problems on the pattern of human Intelligence. This paper draws on employing algorithms such as Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) to generate a hybrid algorithm inspired by the characteristics of these two. Finally simulations have been drawn graphically to compare the energy consumption patterns for appliance scheduling schemes as well as corresponding cost analysis for energy optimization.
Qazi Zafar Iqbal
added 2 research items
This paper presents real time information based energy management algorithms to reduce electricity cost and peak to average ratio (PAR) while preserving user comfort in a smart home. We categorize household appliances into thermostatically controlled (tc), user aware (ua), elastic (el), inelastic (iel) and regular (r) appliances/loads. An optimization problem is formulated to reduce electricity cost by determining the optimal use of household appliances. The operational schedules of these appliances are optimized in response to the electricity price signals and customer preferences to maximize electricity cost saving and user comfort while minimizing curtailed energy. Mathematical optimization models of tc appliances, i.e., air-conditioner and refrigerator, are proposed which are solved by using intelligent programmable communication thermostat ( iPCT). We add extra intelligence to conventional programmable communication thermostat (CPCT) by using genetic algorithm (GA) to control tc appliances under comfort constraints. The optimization models for ua, el, and iel appliances are solved subject to electricity cost minimization and PAR reduction. Considering user comfort, el appliances are considered where users can adjust appliance waiting time to increase or decrease their comfort level. Furthermore, energy demand of r appliances is fulfilled via local supply where the major objective is to reduce the fuel cost of various generators by proper scheduling. Simulation results show that the proposed algorithms efficiently schedule the energy demand of all types of appliances by considering identified constraints (i.e., PAR, variable prices, temperature, capacity limit and waiting time).
In this paper, we introduce a generic architecture for demand side management (DSM) and use combined model of time of use tariff and inclined block rates. The problem formulation is carried via multiple knapsack and its solution is obtained via ant colony optimization (ACO). Simulation results show that the designed model for energy management achieves our objectives; it is proven as a cost-effective solution to increase sustainability of smart grid. The ACO based energy management controller performs more efficiently than energy management controller without ACO based scheduling in terms of electricity bill reduction, peak to average ratio minimization and user comfort level maximization.
Qazi Zafar Iqbal
added 2 research items
In this paper we propose an ECG optimization model for a smart home based on DSM.The proposed model is an efficient SHEM strategy. The model is proposed keeping in view the minimization of energy consumption,energy consumption cost and energy generation cost.The model is based on efficient scheduling of appliances and an ECG optimization algorithm is proposed.We are using and optimizing energy from two energy sources namely lceg and lcd which are also known as macrogrid and microgrid respectively.The problem is solved as cost optimization problem using genetic algorithm and mathematically formulated using binary MNKP. The simulation results show that our ECG model efficiently reduces the cost of energy consumption, energy generation and energy consumption utilization.
Due to smart grid applications the consumers and producers are able to meet the demand of each others and thus take part in demand side management and demand response program. Hence smart grid leads to optimization of energy consumption and reduce high cost in today extensive demand of energy. In this research work we are reducing electricity consumption cost and load consumption using scheduling the appliances. The twenty appliances are used to schedule their energy consumption and load using heuristics techniques i.e. binary particle optimization, genetic algorithm and wind driven optimization, using the same data set for each technique and their results are compared with each other in order to find which technique do better optimization. Simulations are performed in matlab to show the cost and load reduction by the above three techniques and validate the experiment. The simulation results show that binary particle swarm optimization perform better than the other two techniques and wind driven optimization is better than genetic algorithm but not able to perform as binary particle swarm optimization, similarly genetic algorithm is least efficient as compared to both methods. Our research work is beneficial to meet the demand side management and help in reducing electricity cost and load for consumers.
Qazi Zafar Iqbal
added a research item
Question
I want to save below values into mat file in Matlab ,please need suggestions and comments. 0 0 0 0 0 0 0.02558 0.29763 0.61128 0.88163 1.09025 1.22294 1.27064 1.271712308 1.394045385 1.516378462 1.638711538 1.761044615 1.883377692 2.005710769 2.128043846 2.250376923 2.37271 2.495043077 2.617376154 2.739709231 2.862042308 2.984375385 3.106708462 3.229041538 3.351374615 3.473707692 3.596040769 3.718373846 3.840706923 3.96304 4.085373077 4.207706154 4.330039231 4.452372308 4.574705385 4.697038462 4.819371538 4.941704615 5.064037692 5.186370769 5.308703846 5.431036923 5.55337 5.675703077 5.798036154 5.920369231 6.042702308 6.165035385 6.287368462 6.409701538 6.532034615 6.654367692 6.776700769 6.899033846 7.021366923 7.1437 7.266033077 7.388366154 7.510699231 7.633032308 7.755365385 7.877698462 8.000031538 8.122364615 8.244697692 8.367030769 8.489363846 8.611696923 8.73403 8.856363077 8.978696154 9.101029231 9.223362308 9.345695385 9.468028462 9.590361538 9.712694615 9.835027692 9.957360769 10.07969385 10.20202692 10.32436 10.44669308 10.56902615 10.69135923 10.81369231 10.93602538 11.05835846 11.18069154 11.30302462 11.42535769 11.54769077 11.67002385 11.79235692 11.91469 12.03702308 12.15935615 12.28168923 12.40402231 12.52635538 12.64868846 12.77102154 12.89335462 13.01568769 13.13802077 13.26035385 13.38268692 13.50502 13.62735308 13.74968615 13.87201923 13.99435231 14.11668538 14.23901846 14.36135154 14.48368462 14.60601769 14.72835077 14.85068385 14.97301692 15.09535 15.21768308 15.34001615 15.46234923 15.58468231 15.70701538 15.82934846 15.95168154 16.07401462 16.19634769 16.31868077 16.44101385 16.56334692 16.68568 16.80801308 16.93034615 17.05267923 17.17501231 17.29734538 17.41967846 17.54201154 17.66434462 17.78667769 17.90901077 18.03134385 18.15367692 18.27601 18.39834308 18.52067615 18.64300923 18.76534231 18.88767538 19.01000846 19.13234154 19.25467462 19.37700769 19.49934077 19.62167385 19.74400692 19.86634 19.98867308 20.11100615 20.23333923 20.35567231 20.47800538 20.60033846 20.72267154 20.84500462 20.96733769 21.08967077 21.21200385 21.33433692 21.45667 21.57900308 21.70133615 21.82366923 21.94600231 22.06833538 22.19066846 22.31300154 22.43533462 22.55766769 22.68000077 22.80233385 22.92466692 23.047 23.16933308 23.29166615 23.41399923 23.53633231 23.65866538 23.78099846 23.90333154 24.02566462 24.14799769 24.27033077 24.39266385 24.51499692 24.63733 24.75966308 24.88199615 25.00432923 25.12666231 25.24899538 25.37132846 25.49366154 25.61599462 25.73832769 25.86066077 25.98299385 26.10532692 26.22766 26.34999308 26.47232615 26.59465923 26.71699231 26.83932538 26.96165846 27.08399154 27.20632462 27.32865769 27.45099077 27.57332385 27.69565692 27.81799 27.94032308 28.06265615 28.18498923 28.30732231 28.42965538 28.55198846 28.67432154 28.79665462 28.91898769 29.04132077 29.16365385 29.28598692 29.40832 29.53065308 29.65298615 29.77531923 29.89765231 30.01998538 30.14231846 30.26465154 30.38698462 30.50931769 30.63165077 30.75398385 30.87631692 30.99865 31.12098308 31.24331615 31.36564923 31.48798231 31.61031538 31.73264846 31.85498154 31.97731462 32.09964769 32.22198077 32.34431385 32.46664692 32.58898 32.71131308 32.83364615 32.95597923 33.07831231 33.20064538 33.32297846 33.44531154 33.56764462 33.68997769 33.81231077 33.93464385 34.05697692 34.17931 34.30164308 34.42397615 34.54630923 34.66864231 34.79097538 34.91330846 35.03564154 35.15797462 35.28030769 35.40264077 35.52497385 35.64730692 35.76964 35.89197308 36.01430615 36.13663923 36.25897231 36.38130538 36.50363846 36.62597154 36.74830462 36.87063769 36.99297077 37.11530385 37.23763692 37.35997 37.48230308 37.60463615 37.72696923 37.84930231 37.97163538 38.09396846 38.21630154 38.33863462 38.46096769 38.58330077 38.70563385 38.82796692 38.9503 39.07263308 39.19496615 39.31729923 39.43963231 39.56196538 39.68429846 39.80663154 39.92896462 40.05129769 40.17363077 40.29596385 40.41829692 40.54063 40.66296308 40.78529615 40.90762923 41.02996231 41.15229538 41.27462846 41.39696154 41.51929462 41.64162769 41.76396077 41.88629385 42.00862692 42.13096 42.25329308 42.37562615 42.49795923 42.62029231 42.74262538 42.86495846 42.98729154 43.10962462 43.23195769 43.35429077 43.47662385 43.59895692 43.72129 43.84362308 43.96595615 44.08828923 44.21062231 44.33295538 44.45528846 44.57762154 44.69995462 44.82228769 44.94462077 45.06695385 45.18928692 45.31162 45.43395308 45.55628615 45.67861923 45.80095231 45.92328538 46.04561846 46.16795154 46.29028462 46.41261769 46.53495077 46.65728385 46.77961692 46.90195 47.02428308 47.14661615 47.26894923 47.39128231 47.51361538 47.63594846 47.75828154 47.88061462 48.00294769 48.12528077 48.24761385 48.36994692 48.49228 48.61461308 48.73694615 48.85927923 48.98161231 49.10394538 49.22627846 49.34861154 49.47094462 49.59327769 49.71561077 49.83794385 49.96027692 50.08261 50.20494308 50.32727615 50.44960923 50.57194231 50.69427538 50.81660846 50.93894154 51.06127462 51.18360769 51.30594077 51.42827385 51.55060692 51.67294 51.79527308 51.91760615 52.03993923 52.16227231 52.28460538 52.40693846 52.52927154 52.65160462 52.77393769 52.89627077 53.01860385 53.14093692 53.26327 53.38560308 53.50793615 53.63026923 53.75260231 53.87493538 53.99726846 54.11960154 54.24193462 54.36426769 54.48660077 54.60893385 54.73126692 54.8536 54.97593308 55.09826615 55.22059923 55.34293231 55.46526538 55.58759846 55.70993154 55.83226462 55.95459769 56.07693077 56.19926385 56.32159692 56.44393 56.56626308 56.68859615 56.81092923 56.93326231 57.05559538 57.17792846 57.30026154 57.42259462 57.54492769 57.66726077 57.78959385 57.91192692 58.03426 58.15659308 58.27892615 58.40125923 58.52359231 58.64592538 58.76825846 58.89059154 59.01292462 59.13525769 59.25759077 59.37992385 59.50225692 59.62459 59.74692308 59.86925615 59.99158923 60.11392231 60.23625538 60.35858846 60.48092154 60.60325462 60.72558769 60.84792077 60.97025385 61.09258692 61.21492 61.33725308 61.45958615 61.58191923 61.70425231 61.82658538 61.94891846 62.07125154 62.19358462 62.31591769 62.43825077 62.56058385 62.68291692 62.80525 62.92758308 63.04991615 63.17224923 63.29458231 63.41691538 63.53924846 63.66158154 63.78391462 63.90624769 64.02858077 64.15091385 64.27324692 64.39558 64.51791308 64.64024615 64.76257923 64.88491231 65.00724538 65.12957846 65.25191154 65.37424462 65.49657769 65.61891077 65.74124385 65.86357692 65.98591 66.10824308 66.23057615 66.35290923 66.47524231 66.59757538 66.71990846 66.84224154 66.96457462 67.08690769 67.20924077 67.33157385 67.45390692 67.57624 67.69857308 67.82090615 67.94323923 68.06557231 68.18790538 68.31023846 68.43257154 68.55490462 68.67723769 68.79957077 68.92190385 69.04423692 69.16657 69.28890308 69.41123615 69.53356923 69.65590231 69.77823538 69.90056846 70.02290154 70.14523462 70.26756769 70.38990077 70.51223385 70.63456692 70.7569 70.87923308 71.00156615 71.12389923 71.24623231 71.36856538 71.49089846 71.61323154 71.73556462 71.85789769 71.98023077 72.10256385 72.22489692 72.34723 72.46956308 72.59189615 72.71422923 72.83656231 72.95889538 73.08122846 73.20356154 73.32589462 73.44822769 73.57056077 73.69289385 73.81522692 73.93756 74.05989308 74.18222615 74.30455923 74.42689231 74.54922538 74.67155846 74.79389154 74.91622462 75.03855769 75.16089077 75.28322385 75.40555692 75.52789 75.65022308 75.77255615 75.89488923 76.01722231 76.13955538 76.26188846 76.38422154 76.50655462 76.62888769 76.75122077 76.87355385 76.99588692 77.11822 77.24055308 77.36288615 77.48521923 77.60755231 77.72988538 77.85221846 77.97455154 78.09688462 78.21921769 78.34155077 78.46388385 78.58621692 78.70855 78.83088308 78.95321615 79.07554923 79.19788231 79.32021538 79.44254846 79.56488154 79.68721462 79.80954769 79.93188077 80.05421385 80.17654692 80.29888 80.42121308 80.54354615 80.66587923 80.78821231 80.91054538 81.03287846 81.15521154 81.27754462 81.39987769 81.52221077 81.64454385 81.76687692 81.88921 82.01154308 82.13387615 82.25620923 82.37854231 82.50087538 82.62320846 82.74554154 82.86787462 82.99020769 83.11254077 83.23487385 83.35720692 83.47954 83.60187308 83.72420615 83.84653923 83.96887231 84.09120538 84.21353846 84.33587154 84.45820462 84.58053769 84.70287077 84.82520385 84.94753692 85.06987 85.19220308 85.31453615 85.43686923 85.55920231 85.68153538 85.80386846 85.92620154 86.04853462 86.17086769 86.29320077 86.41553385 86.53786692 86.6602 86.78253308 86.90486615 87.02719923 87.14953231 87.27186538 87.39419846 87.51653154 87.63886462 87.76119769 87.88353077 88.00586385 88.12819692 88.25053 88.37286308 88.49519615 88.61752923 88.73986231 88.86219538 88.98452846 89.10686154 89.22919462 89.35152769 89.47386077 89.59619385 89.71852692 89.84086 89.96319308 90.08552615 90.20785923 90.33019231 90.45252538 90.57485846 90.69719154 90.81952462 90.94185769 91.06419077 91.18652385 91.30885692 91.43119 91.55352308 91.67585615 91.79818923 91.92052231 92.04285538 92.16518846 92.28752154 92.40985462 92.53218769 92.65452077 92.77685385 92.89918692 93.02152 93.14385308 93.26618615 93.38851923 93.51085231 93.63318538 93.75551846 93.87785154 94.00018462 94.12251769 94.24485077 94.36718385 94.48951692 94.61185 94.73418308 94.85651615 94.97884923 95.10118231 95.22351538 95.34584846 95.46818154 95.59051462 95.71284769 95.83518077 95.95751385 96.07984692 96.20218 96.32451308 96.44684615 96.56917923 96.69151231 96.81384538 96.93617846 97.05851154 97.18084462 97.30317769 97.42551077 97.54784385 97.67017692 97.79251 97.91484308 98.03717615 98.15950923 98.28184231 98.40417538 98.52650846 98.64884154 98.77117462 98.89350769 99.01584077 99.13817385 99.26050692 99.38284 99.50517308 99.62750615 99.74983923 99.87217231 99.99450538 100.1168385 100.2391715 100.3615046 100.4838377 100.6061708 100.7285038 100.8508369 100.97317 101.0955031 101.2178362 101.3401692 101.4625023 101.5848354 101.7071685 101.8295015 101.9518346 102.0741677 102.1965008 102.3188338 102.4411669 102.5635 102.6858331 102.8081662 102.9304992 103.0528323 103.1751654 103.2974985 103.4198315 103.5421646 103.6644977 103.7868308 103.9091638 104.0314969 104.15383 104.2761631 104.3984962 104.5208292 104.6431623 104.7654954 104.8878285 105.0101615 105.1324946 105.2548277 105.3771608 105.4994938 105.6218269 105.74416 105.8664931 105.9888262 106.1111592 106.2334923 106.3558254 106.4781585 106.6004915 106.7228246 106.8451577 106.9674908 107.0898238 107.2121569 107.33449 107.4568231 107.5791562 107.7014892 107.8238223 107.9461554 108.0684885 108.1908215 108.3131546 108.4354877 108.5578208 108.6801538 108.8024869 108.92482 109.0471531 109.1694862 109.2918192 109.4141523 109.5364854 109.6588185 109.7811515 109.9034846 110.0258177 110.1481508 110.2704838 110.3928169 110.51515 110.6374831 110.7598162 110.8821492 111.0044823 111.1268154 111.2491485 111.3714815 111.4938146 111.6161477 111.7384808 111.8608138 111.9831469 112.10548 112.2278131 112.3501462 112.4724792 112.5948123 112.7171454 112.8394785 112.9618115 113.0841446 113.2064777 113.3288108 113.4511438 113.5734769 113.69581 113.8181431 113.9404762 114.0628092 114.1851423 114.3074754 114.4298085 114.5521415 114.6744746 114.7968077 114.9191408 115.0414738 115.1638069 115.28614 115.4084731 115.5308062 115.6531392 115.7754723 115.8978054 116.0201385 116.1424715 116.2648046 116.3871377 116.5094708 116.6318038 116.7541369 116.87647 116.9988031 117.1211362 117.2434692 117.3658023 117.4881354 117.6104685 117.7328015 117.8551346 117.9774677 118.0998008 118.2221338 118.3444669 118.4668 118.5891331 118.7114662 118.8337992 118.9561323 119.0784654 119.2007985 119.3231315 119.4454646 119.5677977 119.6901308 119.8124638 119.9347969 120.05713 120.1794631 120.3017962 120.4241292 120.5464623 120.6687954 120.7911285 120.9134615 121.0357946 121.1581277 121.2804608 121.4027938 121.5251269 121.64746 121.7697931 121.8921262 122.0144592 122.1367923 122.2591254 122.3814585 122.5037915 122.6261246 122.7484577 122.8707908 122.9931238 123.1154569 123.23779 123.3601231 123.4824562 123.6047892 123.7271223 123.8494554 123.9717885 124.0941215 124.2164546 124.3387877 124.4611208 124.5834538 124.7057869 124.82812 124.9504531 125.0727862 125.1951192 125.3174523 125.4397854 125.5621185 125.6844515 125.8067846 125.9291177 126.0514508 126.1737838 126.2961169 126.41845 126.5407831 126.6631162 126.7854492 126.9077823 127.0301154 127.1524485 127.2747815 127.3971146 127.5194477 127.6417808 127.7641138 127.8864469 128.00878 128.1311131 128.2534462 128.3757792 128.4981123 128.6204454 128.7427785 128.8651115 128.9874446 129.1097777 129.2321108 129.3544438 129.4767769 129.59911 129.7214431 129.8437762 129.9661092 130.0884423 130.2107754 130.3331085 130.4554415 130.5777746 130.7001077 130.8224408 130.9447738 131.0671069 131.18944 131.3117731 131.4341062 131.5564392 131.6787723 131.8011054 131.9234385 132.0457715 132.1681046 132.2904377 132.4127708 132.5351038 132.6574369 132.77977 132.9021031 133.0244362 133.1467692 133.2691023 133.3914354 133.5137685 133.6361015 133.7584346 133.8807677 134.0031008 134.1254338 134.2477669 134.3701 134.4924331 134.6147662 134.7370992 134.8594323 134.9817654 135.1040985 135.2264315 135.3487646 135.4710977 135.5934308 135.7157638 135.8380969 135.96043 136.0827631 136.2050962 136.3274292 136.4497623 136.5720954 136.6944285 136.8167615 136.9390946 137.0614277 137.1837608 137.3060938 137.4284269 137.55076 137.6730931 137.7954262 137.9177592 138.0400923 138.1624254 138.2847585 138.4070915 138.5294246 138.6517577 138.7740908 138.8964238 139.0187569 139.14109 139.2634231 139.3857562 139.5080892 139.6304223 139.7527554 139.8750885 139.9974215 140.1197546 140.2420877 140.3644208 140.4867538 140.6090869 140.73142 140.8537531 140.9760862 141.0984192 141.2207523 141.3430854 141.4654185 141.5877515 141.7100846 141.8324177 141.9547508 142.0770838 142.1994169 142.32175 142.4440831 142.5664162 142.6887492 142.8110823 142.9334154 143.0557485 143.1780815 143.3004146 143.4227477 143.5450808 143.6674138 143.7897469 143.91208 144.0344131 144.1567462 144.2790792 144.4014123 144.5237454 144.6460785 144.7684115 144.8907446 145.0130777 145.1354108 145.2577438 145.3800769 145.50241 145.6247431 145.7470762 145.8694092 145.9917423 146.1140754 146.2364085 146.3587415 146.4810746 146.6034077 146.7257408 146.8480738 146.9704069 147.09274 147.2150731 147.3374062 147.4597392 147.5820723 147.7044054 147.8267385 147.9490715 148.0714046 148.1937377 148.3160708 148.4384038 148.5607369 148.68307 148.8054031 148.9277362 149.0500692 149.1724023 149.2947354 149.4170685 149.5394015 149.6617346 149.7840677 149.9064008 150.0287338 150.1510669 150.2734 150.3957331 150.5180662 150.6403992 150.7627323 150.8850654 151.0073985 151.1297315 151.2520646 151.3743977 151.4967308 151.6190638 151.7413969 151.86373 151.9860631 152.1083962 152.2307292 152.3530623 152.4753954 152.5977285 152.7200615 152.8423946 152.9647277 153.0870608 153.2093938 153.3317269 153.45406 153.5763931 153.6987262 153.8210592 153.9433923 154.0657254 154.1880585 154.3103915 154.4327246 154.5550577 154.6773908 154.7997238 154.9220569 155.04439 155.1667231 155.2890562 155.4113892 155.5337223 155.6560554 155.7783885 155.9007215 156.0230546 156.1453877 156.2677208 156.3900538 156.5123869 156.63472 156.7570531 156.8793862 157.0017192 157.1240523 157.2463854 157.3687185 157.4910515 157.6133846 157.7357177 157.8580508 157.9803838 158.1027169 158.22505 158.3473831 158.4697162 158.5920492 158.7143823 158.8367154 158.9590485 159.0813815 159.2037146 159.3260477 159.4483808 159.5707138 159.6930469 159.81538 159.9377131 160.0600462 160.1823792 160.3047123 160.4270454 160.5493785 160.6717115 160.7940446 160.9163777 161.0387108 161.1610438 161.2833769 161.40571 161.5280431 161.6503762 161.7727092 161.8950423 162.0173754 162.1397085 162.2620415 162.3843746 162.5067077 162.6290408 162.7513738 162.8737069 162.99604 163.1183731 163.2407062 163.3630392 163.4853723 163.6077054 163.7300385 163.8523715 163.9747046 164.0970377 164.2193708 164.3417038 164.4640369 164.58637 164.7087031 164.8310362 164.9533692 165.0757023 165.1980354 165.3203685 165.4427015 165.5650346 165.6873677 165.8097008 165.9320338 166.0543669 166.1767 166.2990331 166.4213662 166.5436992 166.6660323 166.7883654 166.9106985 167.0330315 167.1553646 167.2776977 167.4000308 167.5223638 167.6446969 167.76703 167.8893631 168.0116962 168.1340292 168.2563623 168.3786954 168.5010285 168.6233615 168.7456946 168.8680277 168.9903608 169.1126938 169.2350269 169.35736 169.4796931 169.6020262 169.7243592 169.8466923 169.9690254 170.0913585 170.2136915 170.3360246 170.4583577 170.5806908 170.7030238 170.8253569 170.94769 171.0700231 171.1923562 171.3146892 171.4370223 171.5593554 171.6816885 171.8040215 171.9263546 172.0486877 172.1710208 172.2933538 172.4156869 172.53802 172.6603531 172.7826862 172.9050192 173.0273523 173.1496854 173.2720185 173.3943515 173.5166846 173.6390177 173.7613508 173.8836838 174.0060169 174.12835 174.2506831 174.3730162 174.4953492 174.6176823 174.7400154 174.8623485 174.9846815 175.1070146 175.2293477 175.3516808 175.4740138 175.5963469 175.71868 175.8410131 175.9633462 176.0856792 176.2080123 176.3303454 176.4526785 176.5750115 176.6973446 176.8196777 176.9420108 177.0643438 177.1866769 177.30901 177.4313431 177.5536762 177.6760092 177.7983423 177.9206754 178.0430085 178.1653415 178.2876746 178.4100077 178.5323408 178.6546738 178.7770069 178.89934 179.0216731 179.1440062 179.2663392 179.3886723 179.5110054 179.6333385 179.7556715 179.8780046 180.0003377 180.1226708 180.2450038 180.3673369 180.48967 180.6120031 180.7343362 180.8566692 180.9790023 181.1013354 181.2236685 181.3460015 181.4683346 181.5906677 181.7130008 181.8353338 181.9576669 182.08 182.2023331 182.3246662 182.4469992 182.5693323 182.6916654 182.8139985 182.9363315 183.0586646 183.1809977 183.3033308 183.4256638 183.5479969 183.67033 183.7926631 183.9149962 184.0373292 184.1596623 184.2819954 184.4043285 184.5266615 184.6489946 184.7713277 184.8936608 185.0159938 185.1383269 185.26066 185.3829931 185.5053262 185.6276592 185.7499923 185.8723254 185.9946585 186.1169915 186.2393246 186.3616577 186.4839908 186.6063238 186.7286569 186.85099 186.9733231 187.0956562 187.2179892 187.3403223 187.4626554 187.5849885 187.7073215 187.8296546 187.9519877 188.0743208 188.1966538 188.3189869 188.44132 188.5636531 188.6859862 188.8083192 188.9306523 189.0529854 189.1753185 189.2976515 189.4199846 189.5423177 189.6646508 189.7869838 189.9093169 190.03165 190.1539831 190.2763162 190.3986492 190.5209823 190.6433154 190.7656485 190.8879815 191.0103146 191.1326477 191.2549808 191.3773138 191.4996469 191.62198 191.7443131 191.8666462 191.9889792 192.1113123 192.2336454 192.3559785 192.4783115 192.6006446 192.7229777 192.8453108 192.9676438 193.0899769 193.21231 193.3346431 193.4569762 193.5793092 193.7016423 193.8239754 193.9463085 194.0686415 194.1909746 194.3133077 194.4356408 194.5579738 194.6803069 194.80264 194.9249731 195.0473062 195.1696392 195.2919723 195.4143054 195.5366385 195.6589715 195.7813046 195.9036377 196.0259708 196.1483038 196.2706369 196.39297 196.5153031 196.6376362 196.7599692 196.8823023 197.0046354 197.1269685 197.2493015 197.3716346 197.4939677 197.6163008 197.7386338 197.8609669 197.9833 198.1056331 198.2279662 198.3502992 198.4726323 198.5949654 198.7172985 198.8396315 198.9619646 199.0842977 199.2066308 199.3289638 199.4512969 199.57363 199.6959631 199.8182962 199.9406292 200.0629623 200.1852954 200.3076285 200.4299615 200.5522946 200.6746277 200.7969608 200.9192938 201.0416269 201.16396 201.2862931 201.4086262 201.5309592 201.6532923 201.7756254 201.8979585 202.0202915 202.1426246 202.2649577 202.3872908 202.5096238 202.6319569 202.75429 202.8766231 202.9989562 203.1212892 203.2436223 203.3659554 203.4882885 203.6106215 203.7329546 203.8552877 203.9776208 204.0999538 204.2222869 204.34462 204.4669531 204.5892862 204.7116192 204.8339523 204.9562854 205.0786185 205.2009515 205.3232846 205.4456177 205.5679508 205.6902838 205.8126169 205.93495 206.0572831 206.1796162 206.3019492 206.4242823 206.5466154 206.6689485 206.7912815 206.9136146 207.0359477 207.1582808 207.2806138 207.4029469 207.52528 207.6476131 207.7699462 207.8922792 208.0146123 208.1369454 208.2592785 208.3816115 208.5039446 208.6262777 208.7486108 208.8709438 208.9932769 209.11561 209.2379431 209.3602762 209.4826092 209.6049423 209.7272754 209.8496085 209.9719415 210.0942746 210.2166077 210.3389408 210.4612738 210.5836069 210.70594 210.8282731 210.9506062 211.0729392 211.1952723 211.3176054 211.4399385 211.5622715 211.6846046 211.8069377 211.9292708 212.0516038 212.1739369 212.29627 212.4186031 212.5409362 212.6632692 212.7856023 212.9079354 213.0302685 213.1526015 213.2749346 213.3972677 213.5196008 213.6419338 213.7642669 213.8866 214.0089331 214.1312662 214.2535992 214.3759323 214.4982654 214.6205985 214.7429315 214.8652646 214.9875977 215.1099308 215.2322638 215.3545969 215.47693 215.5992631 215.7215962 215.8439292 215.9662623 216.0885954 216.2109285 216.3332615 216.4555946 216.5779277 216.7002608 216.8225938 216.9449269 217.06726 217.1895931 217.3119262 217.4342592 217.5565923 217.6789254 217.8012585 217.9235915 218.0459246 218.1682577 218.2905908 218.4129238 218.5352569 218.65759 218.7799231 218.9022562 219.0245892 219.1469223 219.2692554 219.3915885 219.5139215 219.6362546 219.7585877 219.8809208 220.0032538 220.1255869 220.24792 220.3702531 220.4925862 220.6149192 220.7372523 220.8595854 220.9819185 221.1042515 221.2265846 221.3489177 221.4712508 221.5935838 221.7159169 221.83825 221.9605831 222.0829162 222.2052492 222.3275823 222.4499154 222.5722485 222.6945815 222.8169146 222.9392477 223.0615808 223.1839138 223.3062469 223.42858 223.5509131 223.6732462 223.7955792 223.9179123 224.0402454 224.1625785 224.2849115 224.4072446 224.5295777 224.6519108 224.7742438 224.8965769 225.01891 225.1412431 225.2635762 225.3859092 225.5082423 225.6305754 225.7529085 225.8752415 225.9975746 226.1199077 226.2422408 226.3645738 226.4869069 226.60924 226.7315731 226.8539062 226.9762392 227.0985723 227.2209054 227.3432385 227.4655715 227.5879046 227.7102377 227.8325708 227.9549038 228.0772369 228.19957 228.3219031 228.4442362 228.5665692 228.6889023 228.8112354 228.9335685 229.0559015 229.1782346 229.3005677 229.4229008 229.5452338 229.6675669 229.7899 229.9122331 230.0345662 230.1568992 230.2792323 230.4015654 230.5238985 230.6462315 230.7685646 230.8908977 231.0132308 231.1355638 231.2578969 231.38023 231.5025631 231.6248962 231.7472292 231.8695623 231.9918954 232.1142285 232.2365615 232.3588946 232.4812277 232.6035608 232.7258938 232.8482269 232.97056 233.0928931 233.2152262 233.3375592 233.4598923 233.5822254 233.7045585 233.8268915 233.9492246 234.0715577 234.1938908 234.3162238 234.4385569 234.56089 234.6832231 234.8055562 234.9278892 235.0502223 235.1725554 235.2948885 235.4172215 235.5395546 235.6618877 235.7842208 235.9065538 236.0288869 236.15122 236.2735531 236.3958862 236.5182192 236.6405523 236.7628854 236.8852185 237.0075515 237.1298846 237.2522177 237.3745508 237.4968838 237.6192169 237.74155 237.8638831 237.9862162 238.1085492 238.2308823 238.3532154 238.4755485 238.5978815 238.7202146 238.8425477 238.9648808 239.0872138 239.2095469 239.33188 239.4542131 239.5765462 239.6988792 239.8212123 239.9435454 240.0658785 240.1882115 240.3105446 240.4328777 240.5552108 240.6775438 240.7998769 240.92221 241.0445431 241.1668762 241.2892092 241.4115423 241.5338754 241.6562085 241.7785415 241.9008746 242.0232077 242.1455408 242.2678738 242.3902069 242.51254 242.6348731 242.7572062 242.8795392 243.0018723 243.1242054 243.2465385 243.3688715 243.4912046 243.6135377 243.7358708 243.8582038 243.9805369 244.10287 244.2252031 244.3475362 244.4698692 244.5922023 244.7145354 244.8368685 244.9592015 245.0815346 245.2038677 245.3262008 245.4485338 245.5708669 245.6932 245.8155331 245.9378662 246.0601992 246.1825323 246.3048654 246.4271985 246.5495315 246.6718646 246.7941977 246.9165308 247.0388638 247.1611969 247.28353 247.4058631 247.5281962 247.6505292 247.7728623 247.8951954 248.0175285 248.1398615 248.2621946 248.3845277 248.5068608 248.6291938 248.7515269 248.87386 248.9961931 249.1185262 249.2408592 249.3631923 249.4855254 249.6078585 249.7301915 249.8525246 249.9748577 250.0971908 250.2195238 250.3418569 250.46419 250.5865231 250.7088562 250.8311892 250.9535223 251.0758554 251.1981885 251.3205215 251.4428546 251.5651877 251.6875208 251.8098538 251.9321869 252.05452 252.1768531 252.2991862 252.4215192 252.5438523 252.6661854 252.7885185 252.9108515 253.0331846 253.1555177 253.2778508 253.4001838 253.5225169 253.64485 253.7671831 253.8895162 254.0118492 254.1341823 254.2565154 254.3788485 254.5011815 254.6235146 254.7458477 254.8681808 254.9905138 255.1128469 255.23518 255.3575131 255.4798462 255.6021792 255.7245123 255.8468454 255.9691785 256.0915115 256.2138446 256.3361777 256.4585108 256.5808438 256.7031769 256.82551 256.9478431 257.0701762 257.1925092 257.3148423 257.4371754 257.5595085 257.6818415 257.8041746 257.9265077 258.0488408 258.1711738 258.2935069 258.41584 258.5381731 258.6605062 258.7828392 258.9051723 259.0275054 259.1498385 259.2721715 259.3945046 259.5168377 259.6391708 259.7615038 259.8838369 260.00617 260.1285031 260.2508362 260.3731692 260.4955023 260.6178354 260.7401685 260.8625015 260.9848346 261.1071677 261.2295008 261.3518338 261.4741669 261.5965 261.7188331 261.8411662 261.9634992 262.0858323 262.2081654 262.3304985 262.4528315 262.5751646 262.6974977 262.8198308 262.9421638 263.0644969 263.18683 263.3091631 263.4314962 263.5538292 263.6761623 263.7984954 263.9208285 264.0431615 264.1654946 264.2878277 264.4101608 264.5324938 264.6548269 264.77716 264.8994931 265.0218262 265.1441592 265.2664923 265.3888254 265.5111585 265.6334915 265.7558246 265.8781577 266.0004908 266.1228238 266.2451569 266.36749 266.4898231 266.6121562 266.7344892 266.8568223 266.9791554 267.1014885 267.2238215 267.3461546 267.4684877 267.5908208 267.7131538 267.8354869 267.95782 268.0801531 268.2024862 268.3248192 268.4471523 268.5694854 268.6918185 268.8141515 268.9364846 269.0588177 269.1811508 269.3034838 269.4258169 269.54815 269.6704831 269.7928162 269.9151492 270.0374823 270.1598154 270.2821485 270.4044815 270.5268146 270.6491477 270.7714808 270.8938138 271.0161469 271.13848 271.2608131 271.3831462 271.5054792 271.6278123 271.7501454 271.8724785 271.9948115 272.1171446 272.2394777 272.3618108 272.4841438 272.6064769 272.72881 272.8511431 272.9734762 273.0958092 273.2181423 273.3404754 273.4628085 273.5851415 273.7074746 273.8298077 273.9521408 274.0744738 274.1968069 274.31914 274.4414731 274.5638062 274.6861392 274.8084723 274.9308054 275.0531385 275.1754715 275.2978046 275.4201377 275.5424708 275.6648038 275.7871369 275.90947 276.0318031 276.1541362 276.2764692 276.3988023 276.5211354 276.6434685 276.7658015 276.8881346 277.0104677 277.1328008 277.2551338 277.3774669 277.4998 277.6221331 277.7444662 277.8667992 277.9891323 278.1114654 278.2337985 278.3561315 278.4784646 278.6007977 278.7231308 278.8454638 278.9677969 279.09013 279.2124631 279.3347962 279.4571292 279.5794623 279.7017954 279.8241285 279.9464615 280.0687946 280.1911277 280.3134608 280.4357938 280.5581269 280.68046 280.8027931 280.9251262 281.0474592 281.1697923 281.2921254 281.4144585 281.5367915 281.6591246 281.7814577 281.9037908 282.0261238 282.1484569 282.27079 282.3931231 282.5154562 282.6377892 282.7601223 282.8824554 283.0047885 283.1271215 283.2494546 283.3717877 283.4941208 283.6164538 283.7387869 283.86112 283.9834531 284.1057862 284.2281192 284.3504523 284.4727854 284.5951185 284.7174515 284.8397846 284.9621177 285.0844508 285.2067838 285.3291169 285.45145 285.5737831 285.6961162 285.8184492 285.9407823 286.0631154 286.1854485 286.3077815 286.4301146 286.5524477 286.6747808 286.7971138 286.9194469 287.04178 287.1641131 287.2864462 287.4087792 287.5311123 287.6534454 287.7757785 287.8981115 288.0204446 288.1427777 288.2651108 288.3874438 288.5097769 288.63211 288.7544431 288.8767762 288.9991092 289.1214423 289.2437754 289.3661085 289.4884415 289.6107746 289.7331077 289.8554408 289.9777738 290.1001069 290.22244 290.3447731 290.4671062 290.5894392 290.7117723 290.8341054 290.9564385 291.0787715 291.2011046 291.3234377 291.4457708 291.5681038 291.6904369 291.81277 291.9351031 292.0574362 292.1797692 292.3021023 292.4244354 292.5467685 292.6691015 292.7914346 292.9137677 293.0361008 293.1584338 293.2807669 293.4031 293.5254331 293.6477662 293.7700992 293.8924323 294.0147654 294.1370985 294.2594315 294.3817646 294.5040977 294.6264308 294.7487638 294.8710969 294.99343 295.1157631 295.2380962 295.3604292 295.4827623 295.6050954 295.7274285 295.8497615 295.9720946 296.0944277 296.2167608 296.3390938 296.4614269 296.58376 296.7060931 296.8284262 296.9507592 297.0730923 297.1954254 297.3177585 297.4400915 297.5624246 297.6847577 297.8070908 297.9294238 298.0517569 298.17409 298.2964231 298.4187562 298.5410892 298.6634223 298.7857554 298.9080885 299.0304215 299.1527546 299.2750877 299.3974208 299.5197538 299.6420869 299.76442 299.8867531 300.0090862 300.1314192 300.2537523 300.3760854 300.4984185 300.6207515 300.7430846 300.8654177 300.9877508 301.1100838 301.2324169 301.35475 301.4770831 301.5994162 301.7217492 301.8440823 301.9664154 302.0887485 302.2110815 302.3334146 302.4557477 302.5780808 302.7004138 302.8227469 302.94508 303.0674131 303.1897462 303.3120792 303.4344123 303.5567454 303.6790785 303.8014115 303.9237446 304.0460777 304.1684108 304.2907438 304.4130769 304.53541 304.6577431 304.7800762 304.9024092 305.0247423 305.1470754 305.2694085 305.3917415 305.5140746 305.6364077 305.7587408 305.8810738 306.0034069 306.12574 306.2480731 306.3704062 306.4927392 306.6150723 306.7374054 306.8597385 306.9820715 307.1044046 307.2267377 307.3490708 307.4714038 307.5937369 307.71607 307.8384031 307.9607362 308.0830692 308.2054023 308.3277354 308.4500685 308.5724015 308.6947346 308.8170677 308.9394008 309.0617338 309.1840669 309.3064 309.4287331 309.5510662 309.6733992 309.7957323 309.9180654 310.0403985 310.1627315 310.2850646 310.4073977 310.5297308 310.6520638 310.7743969 310.89673 311.0190631 311.1413962 311.2637292 311.3860623 311.5083954 311.6307285 311.7530615 311.8753946 311.9977277 312.1200608 312.2423938 312.3647269 312.48706 312.6093931 312.7317262 312.8540592 312.9763923 313.0987254 313.2210585 313.3433915 313.4657246 313.5880577 313.7103908 313.8327238 313.9550569 314.07739 314.1997231 314.3220562 314.4443892 314.5667223 314.6890554 314.8113885 314.9337215 315.0560546 315.1783877 315.3007208 315.4230538 315.5453869 315.66772 315.7900531 315.9123862 316.0347192 316.1570523 316.2793854 316.4017185 316.5240515 316.6463846 316.7687177 316.8910508 317.0133838 317.1357169 317.25805 317.3803831 317.5027162 317.6250492 317.7473823 317.8697154 317.9920485 318.1143815 318.2367146 318.3590477 318.4813808 318.6037138 318.7260469 318.84838 318.9707131 319.0930462 319.2153792 319.3377123 319.4600454 319.5823785 319.7047115 319.8270446 319.9493777 320.0717108 320.1940438 320.3163769 320.43871 320.5610431 320.6833762 320.8057092 320.9280423 321.0503754 321.1727085 321.2950415 321.4173746 321.5397077 321.6620408 321.7843738 321.9067069 322.02904 322.1513731 322.2737062 322.3960392 322.5183723 322.6407054 322.7630385 322.8853715 323.0077046 323.1300377 323.2523708 323.3747038 323.4970369 323.61937 323.7417031 323.8640362 323.9863692 324.1087023 324.2310354 324.3533685 324.4757015 324.5980346 324.7203677 324.8427008 324.9650338 325.0873669 325.2097 325.3320331 325.4543662 325.5766992 325.6990323 325.8213654 325.9436985 326.0660315 326.1883646 326.3106977 326.4330308 326.5553638 326.6776969 326.80003 326.9223631 327.0446962 327.1670292 327.2893623 327.4116954 327.5340285 327.6563615 327.7786946 327.9010277 328.0233608 328.1456938 328.2680269 328.39036 328.5126931 328.6350262 328.7573592 328.8796923 329.0020254 329.1243585 329.2466915 329.3690246 329.4913577 329.6136908 329.7360238 329.8583569 329.98069 330.1030231 330.2253562 330.3476892 330.4700223 330.5923554 330.7146885 330.8370215 330.9593546 331.0816877 331.2040208 331.3263538 331.4486869 331.57102 331.6933531 331.8156862 331.9380192 332.0603523 332.1826854 332.3050185 332.4273515 332.5496846 332.6720177 332.7943508 332.9166838 333.0390169 333.16135 333.2836831 333.4060162 333.5283492 333.6506823 333.7730154 333.8953485 334.0176815 334.1400146 334.2623477 334.3846808 334.5070138 334.6293469 334.75168 334.8740131 334.9963462 335.1186792 335.2410123 335.3633454 335.4856785 335.6080115 335.7303446 335.8526777 335.9750108 336.0973438 336.2196769 336.34201 336.4643431 336.5866762 336.7090092 336.8313423 336.9536754 337.0760085 337.1983415 337.3206746 337.4430077 337.5653408 337.6876738 337.8100069 337.93234 338.0546731 338.1770062 338.2993392 338.4216723 338.5440054 338.6663385 338.7886715 338.9110046 339.0333377 339.1556708 339.2780038 339.4003369 339.52267 339.6450031 339.7673362 339.8896692 340.0120023 340.1343354 340.2566685 340.3790015 340.5013346 340.6236677 340.7460008 340.8683338 340.9906669 341.113 341.2353331 341.3576662 341.4799992 341.6023323 341.7246654 341.8469985 341.9693315 342.0916646 342.2139977 342.3363308 342.4586638 342.5809969 342.70333 342.8256631 342.9479962 343.0703292 343.1926623 343.3149954 343.4373285 343.5596615 343.6819946 343.8043277 343.9266608 344.0489938 344.1713269 344.29366 344.4159931 344.5383262 344.6606592 344.7829923 344.9053254 345.0276585 345.1499915 345.2723246 345.3946577 345.5169908 345.6393238 345.7616569 345.88399 346.0063231 346.1286562 346.2509892 346.3733223 346.4956554 346.6179885 346.7403215 346.8626546 346.9849877 347.1073208 347.2296538 347.3519869 347.47432 347.5966531 347.7189862 347.8413192 347.9636523 348.0859854 348.2083185 348.3306515 348.4529846 348.5753177 348.6976508 348.8199838 348.9423169 349.06465 349.1869831 349.3093162 349.4316492 349.5539823 349.6763154 349.7986485 349.9209815 350.0433146 350.1656477 350.2879808 350.4103138 350.5326469 350.65498 350.7773131 350.8996462 351.0219792 351.1443123 351.2666454 351.3889785 351.5113115 351.6336446 351.7559777 351.8783108 352.0006438 352.1229769 352.24531 352.3676431 352.4899762 352.6123092 352.7346423 352.8569754 352.9793085 353.1016415 353.2239746 353.3463077 353.4686408 353.5909738 353.7133069 353.83564 353.9579731 354.0803062 354.2026392 354.3249723 354.4473054 354.5696385 354.6919715 354.8143046 354.9366377 355.0589708 355.1813038 355.3036369 355.42597 355.5483031 355.6706362 355.7929692 355.9153023 356.0376354 356.1599685 356.2823015 356.4046346 356.5269677 356.6493008 356.7716338 356.8939669 357.0163 357.1386331 357.2609662 357.3832992 357.5056323 357.6279654 357.7502985 357.8726315 357.9949646 358.1172977 358.2396308 358.3619638 358.4842969 358.60663 358.7289631 358.8512962 358.9736292 359.0959623 359.2182954 359.3406285 359.4629615 359.5852946 359.7076277 359.8299608 359.9522938 360.0746269 360.19696 360.3192931 360.4416262 360.5639592 360.6862923 360.8086254 360.9309585 361.0532915 361.1756246 361.2979577 361.4202908 361.5426238 361.6649569 361.78729 361.9096231 362.0319562 362.1542892 362.2766223 362.3989554 362.5212885 362.6436215 362.7659546 362.8882877 363.0106208 363.1329538 363.2552869 363.37762 363.4999531 363.6222862 363.7446192 363.8669523 363.9892854 364.1116185 364.2339515 364.3562846 364.4786177 364.6009508 364.7232838 364.8456169 364.96795 365.0902831 365.2126162 365.3349492 365.4572823 365.5796154 365.7019485 365.8242815 365.9466146 366.0689477 366.1912808 366.3136138 366.4359469 366.55828 366.6806131 366.8029462 366.9252792 367.0476123 367.1699454 367.2922785 367.4146115 367.5369446 367.6592777 367.7816108 367.9039438 368.0262769 368.14861 368.2709431 368.3932762 368.5156092 368.6379423 368.7602754 368.8826085 369.0049415 369.1272746 369.2496077 369.3719408 369.4942738 369.6166069 369.73894 369.8612731 369.9836062 370.1059392 370.2282723 370.3506054 370.4729385 370.5952715 370.7176046 370.8399377 370.9622708 371.0846038 371.2069369 371.32927 371.4516031 371.5739362 371.6962692 371.8186023 371.9409354 372.0632685 372.1856015 372.3079346 372.4302677 372.5526008 372.6749338 372.7972669 372.9196 373.0419331 373.1642662 373.2865992 373.4089323 373.5312654 373.6535985 373.7759315 373.8982646 374.0205977 374.1429308 374.2652638 374.3875969 374.50993 374.6322631 374.7545962 374.8769292 374.9992623 375.1215954 375.2439285 375.3662615 375.4885946 375.6109277 375.7332608 375.8555938 375.9779269 376.10026 376.2225931 376.3449262 376.4672592 376.5895923 376.7119254 376.8342585 376.9565915 377.0789246 377.2012577 377.3235908 377.4459238 377.5682569 377.69059 377.8129231 377.9352562 378.0575892 378.1799223 378.3022554 378.4245885 378.5469215 378.6692546 378.7915877 378.9139208 379.0362538 379.1585869 379.28092 379.4032531 379.5255862 379.6479192 379.7702523 379.8925854 380.0149185 380.1372515 380.2595846 380.3819177 380.5042508 380.6265838 380.7489169 380.87125 380.9935831 381.1159162 381.2382492 381.3605823 381.4829154 381.6052485 381.7275815 381.8499146 381.9722477 382.0945808 382.2169138 382.3392469 382.46158 382.5839131 382.7062462 382.8285792 382.9509123 383.0732454 383.1955785 383.3179115 383.4402446 383.5625777 383.6849108 383.8072438 383.9295769 384.05191 384.1742431 384.2965762 384.4189092 384.5412423 384.6635754 384.7859085 384.9082415 385.0305746 385.1529077 385.2752408 385.3975738 385.5199069 385.64224 385.7645731 385.8869062 386.0092392 386.1315723 386.2539054 386.3762385 386.4985715 386.6209046 386.7432377 386.8655708 386.9879038 387.1102369 387.23257 387.3549031 387.4772362 387.5995692 387.7219023 387.8442354 387.9665685 388.0889015 388.2112346 388.3335677 388.4559008 388.5782338 388.7005669 388.8229 388.9452331 389.0675662 389.1898992 389.3122323 389.4345654 389.5568985 389.6792315 389.8015646 389.9238977 390.0462308 390.1685638 390.2908969 390.41323 390.5355631 390.6578962 390.7802292 390.9025623 391.0248954 391.1472285 391.2695615 391.3918946 391.5142277 391.6365608 391.7588938 391.8812269 392.00356 392.1258931 392.2482262 392.3705592 392.4928923 392.6152254 392.7375585 392.8598915 392.9822246 393.1045577 393.2268908 393.3492238 393.4715569 393.59389 393.7162231 393.8385562 393.9608892 394.0832223 394.2055554 394.3278885 394.4502215 394.5725546 394.6948877 394.8172208 394.9395538 395.0618869 395.18422 395.3065531 395.4288862 395.5512192 395.6735523 395.7958854 395.9182185 396.0405515 396.1628846 396.2852177 396.4075508 396.5298838 396.6522169 396.77455 396.8968831 397.0192162 397.1415492 397.2638823 397.3862154 397.5085485 397.6308815 397.7532146 397.8755477 397.9978808 398.1202138 398.2425469 398.36488 398.4872131 398.6095462 398.7318792 398.8542123 398.9765454 399.0988785 399.2212115 399.3435446 399.4658777 399.5882108 399.7105438 399.8328769 399.95521 400.0775431 400.1998762 400.3222092 400.4445423 400.5668754 400.6892085 400.8115415 400.9338746 401.0562077 401.1785408 401.3008738 401.4232069 401.54554 401.6678731 401.7902062 401.9125392 402.0348723 402.1572054 402.2795385 402.4018715 402.5242046 402.6465377 402.7688708 402.8912038 403.0135369 403.13587 403.2582031 403.3805362 403.5028692 403.6252023 403.7475354 403.8698685 403.9922015 404.1145346 404.2368677 404.3592008 404.4815338 404.6038669 404.7262 404.8485331 404.9708662 405.0931992 405.2155323 405.3378654 405.4601985 405.5825315 405.7048646 405.8271977 405.9495308 406.0718638 406.1941969 406.31653 406.4388631 406.5611962 406.6835292 406.8058623 406.9281954 407.0505285 407.1728615 407.2951946 407.4175277 407.5398608 407.6621938 407.7845269 407.90686 408.0291931 408.1515262 408.2738592 408.3961923 408.5185254 408.6408585 408.7631915 408.8855246 409.0078577 409.1301908 409.2525238 409.3748569 409.49719 409.6195231 409.7418562 409.8641892 409.9865223 410.1088554 410.2311885 410.3535215 410.4758546 410.5981877 410.7205208 410.8428538 410.9651869 411.08752 411.2098531 411.3321862 411.4545192 411.5768523 411.6991854 411.8215185 411.9438515 412.0661846 412.1885177 412.3108508 412.4331838 412.5555169 412.67785 412.8001831 412.9225162 413.0448492 413.1671823 413.2895154 413.4118485 413.5341815 413.6565146 413.7788477 413.9011808 414.0235138 414.1458469 414.26818 414.3905131 414.5128462 414.6351792 414.7575123 414.8798454 415.0021785 415.1245115 415.2468446 415.3691777 415.4915108 415.6138438 415.7361769 415.85851 415.9808431 416.1031762 416.2255092 416.3478423 416.4701754 416.5925085 416.7148415 416.8371746 416.9595077 417.0818408 417.2041738 417.3265069 417.44884 417.5711731 417.6935062 417.8158392 417.9381723 418.0605054 418.1828385 418.3051715 418.4275046 418.5498377 418.6721708 418.7945038 418.9168369 419.03917 419.1615031 419.2838362 419.4061692 419.5285023 419.6508354 419.7731685 419.8955015 420.0178346 420.1401677 420.2625008 420.3848338 420.5071669 420.6295 420.7518331 420.8741662 420.9964992 421.1188323 421.2411654 421.3634985 421.4858315 421.6081646 421.7304977 421.8528308 421.9751638 422.0974969 422.21983 422.3421631 422.4644962 422.5868292 422.7091623 422.8314954 422.9538285 423.0761615 423.1984946 423.3208277 423.4431608 423.5654938 423.6878269 423.81016 423.9324931 424.0548262 424.1771592 424.2994923 424.4218254 424.5441585 424.6664915 424.7888246 424.9111577 425.0334908 425.1558238 425.2781569 425.40049 425.5228231 425.6451562 425.7674892 425.8898223 426.0121554 426.1344885 426.2568215 426.3791546 426.5014877 426.6238208 426.7461538 426.8684869 426.99082 427.1131531 427.2354862 427.3578192 427.4801523 427.6024854 427.7248185 427.8471515 427.9694846 428.0918177 428.2141508 428.3364838 428.4588169 428.58115 428.7034831 428.8258162 428.9481492 429.0704823 429.1928154 429.3151485 429.4374815 429.5598146 429.6821477 429.8044808 429.9268138 430.0491469 430.17148 430.2938131 430.4161462 430.5384792 430.6608123 430.7831454 430.9054785 431.0278115 431.1501446 431.2724777 431.3948108 431.5171438 431.6394769 431.76181 431.8841431 432.0064762 432.1288092 432.2511423 432.3734754 432.4958085 432.6181415 432.7404746 432.8628077 432.9851408 433.1074738 433.2298069 433.35214 433.4744731 433.5968062 433.7191392 433.8414723 433.9638054 434.0861385 434.2084715 434.3308046 434.4531377 434.5754708 434.6978038 434.8201369 434.94247 435.0648031 435.1871362 435.3094692 435.4318023 435.5541354 435.6764685 435.7988015 435.9211346 436.0434677 436.1658008 436.2881338 436.4104669 436.5328 436.6551331 436.7774662 436.8997992 437.0221323 437.1444654 437.2667985 437.3891315 437.5114646 437.6337977 437.7561308 437.8784638 438.0007969 438.12313 438.2454631 438.3677962 438.4901292 438.6124623 438.7347954 438.8571285 438.9794615 439.1017946 439.2241277 439.3464608 439.4687938 439.5911269 439.71346 439.8357931 439.9581262 440.0804592 440.2027923 440.3251254 440.4474585 440.5697915 440.6921246 440.8144577 440.9367908 441.0591238 441.1814569 441.30379 441.4261231 441.5484562 441.6707892 441.7931223 441.9154554 442.0377885 442.1601215 442.2824546 442.4047877 442.5271208 442.6494538 442.7717869 442.89412 443.0164531 443.1387862 443.2611192 443.3834523 443.5057854 443.6281185 443.7504515 443.8727846 443.9951177 444.1174508 444.2397838 444.3621169 444.48445 444.6067831 444.7291162 444.8514492 444.9737823 445.0961154 445.2184485 445.3407815 445.4631146 445.5854477 445.7077808 445.8301138 445.9524469 446.07478 446.1971131 446.3194462 446.4417792 446.5641123 446.6864454 446.8087785 446.9311115 447.0534446 447.1757777 447.2981108 447.4204438 447.5427769 447.66511 447.7874431 447.9097762 448.0321092 448.1544423 448.2767754 448.3991085 448.5214415 448.6437746 448.7661077 448.8884408 449.0107738 449.1331069 449.25544 449.3777731 449.5001062 449.6224392 449.7447723 449.8671054 449.9894385 450.1117715 450.2341046 450.3564377 450.4787708 450.6011038 450.7234369 450.84577 450.9681031 451.0904362 451.2127692 451.3351023 451.4574354 451.5797685 451.7021015 451.8244346 451.9467677 452.0691008 452.1914338 452.3137669 452.4361 452.5584331 452.6807662 452.8030992 452.9254323 453.0477654 453.1700985 453.2924315 453.4147646 453.5370977 453.6594308 453.7817638 453.9040969 454.02643 454.1487631 454.2710962 454.3934292 454.5157623 454.6380954 454.7604285 454.8827615 455.0050946 455.1274277 455.2497608 455.3720938 455.4944269 455.61676 455.7390931 455.8614262 455.9837592 456.1060923 456.2284254 456.3507585 456.4730915 456.5954246 456.7177577 456.8400908 456.9624238 457.0847569 457.20709 457.3294231 457.4517562 457.5740892 457.6964223 457.8187554 457.9410885 458.0634215 458.1857546 458.3080877 458.4304208 458.5527538 458.6750869 458.79742 458.9197531 459.0420862 459.1644192 459.2867523 459.4090854 459.5314185 459.6537515 459.7760846 459.8984177 460.0207508 460.1430838 460.2654169 460.38775 460.5100831 460.6324162 460.7547492 460.8770823 460.9994154 461.1217485 461.2440815 461.3664146 461.4887477 461.6110808 461.7334138 461.8557469 461.97808 462.1004131 462.2227462 462.3450792 462.4674123 462.5897454 462.7120785 462.8344115 462.9567446 463.0790777 463.2014108 463.3237438 463.4460769 463.56841 463.6907431 463.8130762 463.9354092 464.0577423 464.1800754 464.3024085 464.4247415 464.5470746 464.6694077 464.7917408 464.9140738 465.0364069 465.15874 465.2810731 465.4034062 465.5257392 465.6480723 465.7704054 465.8927385 466.0150715 466.1374046 466.2597377 466.3820708 466.5044038 466.6267369 466.74907 466.8714031 466.9937362 467.1160692 467.2384023 467.3607354 467.4830685 467.6054015 467.7277346 467.8500677 467.9724008 468.0947338 468.2170669 468.3394 468.4617331 468.5840662 468.7063992 468.8287323 468.9510654 469.0733985 469.1957315 469.3180646 469.4403977 469.5627308 469.6850638 469.8073969 469.92973 470.0520631 470.1743962 470.2967292 470.4190623 470.5413954 470.6637285 470.7860615 470.9083946 471.0307277 471.1530608 471.2753938 471.3977269 471.52006 471.6423931 471.7647262 471.8870592 472.0093923 472.1317254 472.2540585 472.3763915 472.4987246 472.6210577 472.7433908 472.8657238 472.9880569 473.11039 473.2327231 473.3550562 473.4773892 473.5997223 473.7220554 473.8443885 473.9667215 474.0890546 474.2113877 474.3337208 474.4560538 474.5783869 474.70072 474.8230531 474.9453862 475.0677192 475.1900523 475.3123854 475.4347185 475.5570515 475.6793846 475.8017177 475.9240508 476.0463838 476.1687169 476.29105 476.4133831 476.5357162 476.6580492 476.7803823 476.9027154 477.0250485 477.1473815 477.2697146 477.3920477 477.5143808 477.6367138 477.7590469 477.88138 478.0037131 478.1260462 478.2483792 478.3707123 478.4930454 478.6153785 478.7377115 478.8600446 478.9823777 479.1047108 479.2270438 479.3493769 479.47171 479.5940431 479.7163762 479.8387092 479.9610423 480.0833754 480.2057085 480.3280415 480.4503746 480.5727077 480.6950408 480.8173738 480.9397069 481.06204 481.1843731 481.3067062 481.4290392 481.5513723 481.6737054 481.7960385 481.9183715 482.0407046 482.1630377 482.2853708 482.4077038 482.5300369 482.65237 482.7747031 482.8970362 483.0193692 483.1417023 483.2640354 483.3863685 483.5087015 483.6310346 483.7533677 483.8757008 483.9980338 484.1203669 484.2427 484.3650331 484.4873662 484.6096992 484.7320323 484.8543654 484.9766985 485.0990315 485.2213646 485.3436977 485.4660308 485.5883638 485.7106969 485.83303 485.9553631 486.0776962 486.2000292 486.3223623 486.4446954 486.5670285 486.6893615 486.8116946 486.9340277 487.0563608 487.1786938 487.3010269 487.42336 487.5456931 487.6680262 487.7903592 487.9126923 488.0350254 488.1573585 488.2796915 488.4020246 488.5243577 488.6466908 488.7690238 488.8913569 489.01369 489.1360231 489.2583562 489.3806892 489.5030223 489.6253554 489.7476885 489.8700215 489.9923546 490.1146877 490.2370208 490.3593538 490.4816869 490.60402 490.7263531 490.8486862 490.9710192 491.0933523 491.2156854 491.3380185 491.4603515 491.5826846 491.7050177 491.8273508 491.9496838 492.0720169 492.19435 492.3166831 492.4390162 492.5613492 492.6836823 492.8060154 492.9283485 493.0506815 493.1730146 493.2953477 493.4176808 493.5400138 493.6623469 493.78468 493.9070131 494.0293462 494.1516792 494.2740123 494.3963454 494.5186785 494.6410115 494.7633446 494.8856777 495.0080108 495.1303438 495.2526769 495.37501 495.4973431 495.6196762 495.7420092 495.8643423 495.9866754 496.1090085 496.2313415 496.3536746 496.4760077 496.5983408 496.7206738 496.8430069 496.96534 497.0876731 497.2100062 497.3323392 497.4546723 497.5770054 497.6993385 497.8216715 497.9440046 498.0663377 498.1886708 498.3110038 498.4333369 498.55567 498.6780031 498.8003362 498.9226692 499.0450023 499.1673354 499.2896685 499.4120015 499.5343346 499.6566677 499.7790008 499.9013338 500.0236669 500.146 500.2683331 500.3906662 500.5129992 500.6353323 500.7576654 500.8799985 501.0023315 501.1246646 501.2469977 501.3693308 501.4916638 501.6139969 501.73633 501.8586631 501.9809962 502.1033292 502.2256623 502.3479954 502.4703285 502.5926615 502.7149946 502.8373277 502.9596608 503.0819938 503.2043269 503.32666 503.4489931 503.5713262 503.6936592 503.8159923 503.9383254 504.0606585 504.1829915 504.3053246 504.4276577 504.5499908 504.6723238 504.7946569 504.91699 505.0393231 505.1616562 505.2839892 505.4063223 505.5286554 505.6509885 505.7733215 505.8956546 506.0179877 506.1403208 506.2626538 506.3849869 506.50732 506.6296531 506.7519862 506.8743192 506.9966523 507.1189854 507.2413185 507.3636515 507.4859846 507.6083177 507.7306508 507.8529838 507.9753169 508.09765 508.2199831 508.3423162 508.4646492 508.5869823 508.7093154 508.8316485 508.9539815 509.0763146 509.1986477 509.3209808 509.4433138 509.5656469 509.68798 509.8103131 509.9326462 510.0549792 510.1773123 510.2996454 510.4219785 510.5443115 510.6666446 510.7889777 510.9113108 511.0336438 511.1559769 511.27831 511.4006431 511.5229762 511.6453092 511.7676423 511.8899754 512.0123085 512.1346415 512.2569746 512.3793077 512.5016408 512.6239738 512.7463069 512.86864 512.9909731 513.1133062 513.2356392 513.3579723 513.4803054 513.6026385 513.7249715 513.8473046 513.9696377 514.0919708 514.2143038 514.3366369 514.45897 514.5813031 514.7036362 514.8259692 514.9483023 515.0706354 515.1929685 515.3153015 515.4376346 515.5599677 515.6823008 515.8046338 515.9269669 516.0493 516.1716331 516.2939662 516.4162992 516.5386323 516.6609654 516.7832985 516.9056315 517.0279646 517.1502977 517.2726308 517.3949638 517.5172969 517.63963 517.7619631 517.8842962 518.0066292 518.1289623 518.2512954 518.3736285 518.4959615 518.6182946 518.7406277 518.8629608 518.9852938 519.1076269 519.22996 519.3522931 519.4746262 519.5969592 519.7192923 519.8416254 519.9639585 520.0862915 520.2086246 520.3309577 520.4532908 520.5756238 520.6979569 520.82029 520.9426231 521.0649562 521.1872892 521.3096223 521.4319554 521.5542885 521.6766215 521.7989546 521.9212877 522.0436208 522.1659538 522.2882869 522.41062 522.5329531 522.6552862 522.7776192 522.8999523 523.0222854 523.1446185 523.2669515 523.3892846 523.5116177 523.6339508 523.7562838 523.8786169 524.00095 524.1232831 524.2456162 524.3679492 524.4902823 524.6126154 524.7349485 524.8572815 524.9796146 525.1019477 525.2242808 525.3466138 525.4689469 525.59128 525.7136131 525.8359462 525.9582792 526.0806123 526.2029454 526.3252785 526.4476115 526.5699446 526.6922777 526.8146108 526.9369438 527.0592769 527.18161 527.3039431 527.4262762 527.5486092 527.6709423 527.7932754 527.9156085 528.0379415 528.1602746 528.2826077 528.4049408 528.5272738 528.6496069 528.77194 528.8942731 529.0166062 529.1389392 529.2612723 529.3836054 529.5059385 529.6282715 529.7506046 529.8729377 529.9952708 530.1176038 530.2399369 530.36227 530.4846031 530.6069362 530.7292692 530.8516023 530.9739354 531.0962685 531.2186015 531.3409346 531.4632677 531.5856008 531.7079338 531.8302669 531.9526 532.0749331 532.1972662 532.3195992 532.4419323 532.5642654 532.6865985 532.8089315 532.9312646 533.0535977 533.1759308 533.2982638 533.4205969 533.54293 533.6652631 533.7875962 533.9099292 534.0322623 534.1545954 534.2769285 534.3992615 534.5215946 534.6439277 534.7662608 534.8885938 535.0109269 535.13326 535.2555931 535.3779262 535.5002592 535.6225923 535.7449254 535.8672585 535.9895915 536.1119246 536.2342577 536.3565908 536.4789238 536.6012569 536.72359 536.8459231 536.9682562 537.0905892 537.2129223 537.3352554 537.4575885 537.5799215 537.7022546 537.8245877 537.9469208 538.0692538 538.1915869 538.31392 538.4362531 538.5585862 538.6809192 538.8032523 538.9255854 539.0479185 539.1702515 539.2925846 539.4149177 539.5372508 539.6595838 539.7819169 539.90425 540.0265831 540.1489162 540.2712492 540.3935823 540.5159154 540.6382485 540.7605815 540.8829146 541.0052477 541.1275808 541.2499138 541.3722469 541.49458 541.6169131 541.7392462 541.8615792 541.9839123 542.1062454 542.2285785 542.3509115 542.4732446 542.5955777 542.7179108 542.8402438 542.9625769 543.08491 543.2072431 543.3295762 543.4519092 543.5742423 543.6965754 543.8189085 543.9412415 544.0635746 544.1859077 544.3082408 544.4305738 544.5529069 544.67524 544.7975731 544.9199062 545.0422392 545.1645723 545.2869054 545.4092385 545.5315715 545.6539046 545.7762377 545.8985708 546.0209038 546.1432369 546.26557 546.3879031 546.5102362 546.6325692 546.7549023 546.8772354 546.9995685 547.1219015 547.2442346 547.3665677 547.4889008 547.6112338 547.7335669 547.8559 547.9782331 548.1005662 548.2228992 548.3452323 548.4675654 548.5898985 548.7122315 548.8345646 548.9568977 549.0792308 549.2015638 549.3238969 549.44623 549.5685631 549.6908962 549.8132292 549.9355623 550.0578954 550.1802285 550.3025615 550.4248946 550.5472277 550.6695608 550.7918938 550.9142269 551.03656 551.1588931 551.2812262 551.4035592 551.5258923 551.6482254 551.7705585 551.8928915 552.0152246 552.1375577 552.2598908 552.3822238 552.5045569 552.62689 552.7492231 552.8715562 552.9938892 553.1162223 553.2385554 553.3608885 553.4832215 553.6055546 553.7278877 553.8502208 553.9725538 554.0948869 554.21722 554.3395531 554.4618862 554.5842192 554.7065523 554.8288854 554.9512185 555.0735515 555.1958846 555.3182177 555.4405508 555.5628838 555.6852169 555.80755 555.9298831 556.0522162 556.1745492 556.2968823 556.4192154 556.5415485 556.6638815 556.7862146 556.9085477 557.0308808 557.1532138 557.2755469 557.39788 557.5202131 557.6425462 557.7648792 557.8872123 558.0095454 558.1318785 558.2542115 558.3765446 558.4988777 558.6212108 558.7435438 558.8658769 558.98821 559.1105431 559.2328762 559.3552092 559.4775423 559.5998754 559.7222085 559.8445415 559.9668746 560.0892077 560.2115408 560.3338738 560.4562069 560.57854 560.7008731 560.8232062 560.9455392 561.0678723 561.1902054 561.3125385 561.4348715 561.5572046 561.6795377 561.8018708 561.9242038 562.0465369 562.16887 562.2912031 562.4135362 562.5358692 562.6582023 562.7805354 562.9028685 563.0252015 563.1475346 563.2698677 563.3922008 563.5145338 563.6368669 563.7592 563.8815331 564.0038662 564.1261992 564.2485323 564.3708654 564.4931985 564.6155315 564.7378646 564.8601977 564.9825308 565.1048638 565.2271969 565.34953 565.4718631 565.5941962 565.7165292 565.8388623 565.9611954 566.0835285 566.2058615 566.3281946 566.4505277 566.5728608 566.6951938 566.8175269 566.93986 567.0621931 567.1845262 567.3068592 567.4291923 567.5515254 567.6738585 567.7961915 567.9185246 568.0408577 568.1631908 568.2855238 568.4078569 568.53019 568.6525231 568.7748562 568.8971892 569.0195223 569.1418554 569.2641885 569.3865215 569.5088546 569.6311877 569.7535208 569.8758538 569.9981869 570.12052 570.2428531 570.3651862 570.4875192 570.6098523 570.7321854 570.8545185 570.9768515 571.0991846 571.2215177 571.3438508 571.4661838 571.5885169 571.71085 571.8331831 571.9555162 572.0778492 572.2001823 572.3225154 572.4448485 572.5671815 572.6895146 572.8118477 572.9341808 573.0565138 573.1788469 573.30118 573.4235131 573.5458462 573.6681792 573.7905123 573.9128454 574.0351785 574.1575115 574.2798446 574.4021777 574.5245108 574.6468438 574.7691769 574.89151 575.0138431 575.1361762 575.2585092 575.3808423 575.5031754 575.6255085 575.7478415 575.8701746 575.9925077 576.1148408 576.2371738 576.3595069 576.48184 576.6041731 576.7265062 576.8488392 576.9711723 577.0935054 577.2158385 577.3381715 577.4605046 577.5828377 577.7051708 577.8275038 577.9498369 578.07217 578.1945031 578.3168362 578.4391692 578.5615023 578.6838354 578.8061685 578.9285015 579.0508346 579.1731677 579.2955008 579.4178338 579.5401669 579.6625 579.7848331 579.9071662 580.0294992 580.1518323 580.2741654 580.3964985 580.5188315 580.6411646 580.7634977 580.8858308 581.0081638 581.1304969 581.25283 581.3751631 581.4974962 581.6198292 581.7421623 581.8644954 581.9868285 582.1091615 582.2314946 582.3538277 582.4761608 582.5984938 582.7208269 582.84316 582.9654931 583.0878262 583.2101592 583.3324923 583.4548254 583.5771585 583.6994915 583.8218246 583.9441577 584.0664908 584.1888238 584.3111569 584.43349 584.5558231 584.6781562 584.8004892 584.9228223 585.0451554 585.1674885 585.2898215 585.4121546 585.5344877 585.6568208 585.7791538 585.9014869 586.02382 586.1461531 586.2684862 586.3908192 586.5131523 586.6354854 586.7578185 586.8801515 587.0024846 587.1248177 587.2471508 587.3694838 587.4918169 587.61415 587.7364831 587.8588162 587.9811492 588.1034823 588.2258154 588.3481485 588.4704815 588.5928146 588.7151477 588.8374808 588.9598138 589.0821469 589.20448 589.3268131 589.4491462 589.5714792 589.6938123 589.8161454 589.9384785 590.0608115 590.1831446 590.3054777 590.4278108 590.5501438 590.6724769 590.79481 590.9171431 591.0394762 591.1618092 591.2841423 591.4064754 591.5288085 591.6511415 591.7734746 591.8958077 592.0181408 592.1404738 592.2628069 592.38514 592.5074731 592.6298062 592.7521392 592.8744723 592.9968054 593.1191385 593.2414715 593.3638046 593.4861377 593.6084708 593.7308038 593.8531369 593.97547 594.0978031 594.2201362 594.3424692 594.4648023 594.5871354 594.7094685 594.8318015 594.9541346 595.0764677 595.1988008 595.3211338 595.4434669 595.5658 595.6881331 595.8104662 595.9327992 596.0551323 596.1774654 596.2997985 596.4221315 596.5444646 596.6667977 596.7891308 596.9114638 597.0337969 597.15613 597.2784631 597.4007962 597.5231292 597.6454623 597.7677954 597.8901285 598.0124615 598.1347946 598.2571277 598.3794608 598.5017938 598.6241269 598.74646 598.8687931 598.9911262 599.1134592 599.2357923 599.3581254 599.4804585 599.6027915 599.7251246 599.8474577 599.9697908 600.0921238 600.2144569 600.33679 600.4591231 600.5814562 600.7037892 600.8261223 600.9484554 601.0707885 601.1931215 601.3154546 601.4377877 601.5601208 601.6824538 601.8047869 601.92712 602.0494531 602.1717862 602.2941192 602.4164523 602.5387854 602.6611185 602.7834515 602.9057846 603.0281177 603.1504508 603.2727838 603.3951169 603.51745 603.6397831 603.7621162 603.8844492 604.0067823 604.1291154 604.2514485 604.3737815 604.4961146 604.6184477 604.7407808 604.8631138 604.9854469 605.10778 605.2301131 605.3524462 605.4747792 605.5971123 605.7194454 605.8417785 605.9641115 606.0864446 606.2087777 606.3311108 606.4534438 606.5757769 606.69811 606.8204431 606.9427762 607.0651092 607.1874423 607.3097754 607.4321085 607.5544415 607.6767746 607.7991077 607.9214408 608.0437738 608.1661069 608.28844 608.4107731 608.5331062 608.6554392 608.7777723 608.9001054 609.0224385 609.1447715 609.2671046 609.3894377 609.5117708 609.6341038 609.7564369 609.87877 610.0011031 610.1234362 610.2457692 610.3681023 610.4904354 610.6127685 610.7351015 610.8574346 610.9797677 611.1021008 611.2244338 611.3467669 611.4691 611.5914331 611.7137662 611.8360992 611.9584323 612.0807654 612.2030985 612.3254315 612.4477646 612.5700977 612.6924308 612.8147638 612.9370969 613.05943 613.1817631 613.3040962 613.4264292 613.5487623 613.6710954 613.7934285 613.9157615 614.0380946 614.1604277 614.2827608 614.4050938 614.5274269 614.64976 614.7720931 614.8944262 615.0167592 615.1390923 615.2614254 615.3837585 615.5060915 615.6284246 615.7507577 615.8730908 615.9954238 616.1177569 616.24009 616.3624231 616.4847562 616.6070892 616.7294223 616.8517554 616.9740885 617.0964215 617.2187546 617.3410877 617.4634208 617.5857538 617.7080869 617.83042 617.9527531 618.0750862 618.1974192 618.3197523 618.4420854 618.5644185 618.6867515 618.8090846 618.9314177 619.0537508 619.1760838 619.2984169 619.42075 619.5430831 619.6654162 619.7877492 619.9100823 620.0324154 620.1547485 620.2770815 620.3994146 620.5217477 620.6440808 620.7664138 620.8887469 621.01108 621.1334131 621.2557462 621.3780792 621.5004123 621.6227454 621.7450785 621.8674115 621.9897446 622.1120777 622.2344108 622.3567438 622.4790769 622.60141 622.7237431 622.8460762 622.9684092 623.0907423 623.2130754 623.3354085 623.4577415 623.5800746 623.7024077 623.8247408 623.9470738 624.0694069 624.19174 624.3140731 624.4364062 624.5587392 624.6810723 624.8034054 624.9257385 625.0480715 625.1704046 625.2927377 625.4150708 625.5374038 625.6597369 625.78207 625.9044031 626.0267362 626.1490692 626.2714023 626.3937354 626.5160685 626.6384015 626.7607346 626.8830677 627.0054008 627.1277338 627.2500669 627.3724 627.4947331 627.6170662 627.7393992 627.8617323 627.9840654 628.1063985 628.2287315 628.3510646 628.4733977 628.5957308 628.7180638 628.8403969 628.96273 629.0850631 629.2073962 629.3297292 629.4520623 629.5743954 629.6967285 629.8190615 629.9413946 630.0637277 630.1860608 630.3083938 630.4307269 630.55306 630.6753931 630.7977262 630.9200592 631.0423923 631.1647254 631.2870585 631.4093915 631.5317246 631.6540577 631.7763908 631.8987238 632.0210569 632.14339 632.2657231 632.3880562 632.5103892 632.6327223 632.7550554 632.8773885 632.9997215 633.1220546 633.2443877 633.3667208 633.4890538 633.6113869 633.73372 633.8560531 633.9783862 634.1007192 634.2230523 634.3453854 634.4677185 634.5900515 634.7123846 634.8347177 634.9570508 635.0793838 635.2017169 635.32405 635.4463831 635.5687162 635.6910492 635.8133823 635.9357154 636.0580485 636.1803815 636.3027146 636.4250477 636.5473808 636.6697138 636.7920469 636.91438 637.0367131 637.1590462 637.2813792 637.4037123 637.5260454 637.6483785 637.7707115 637.8930446 638.0153777 638.1377108 638.2600438 638.3823769 638.50471 638.6270431 638.7493762 638.8717092 638.9940423 639.1163754 639.2387085 639.3610415 639.4833746 639.6057077 639.7280408 639.8503738 639.9727069 640.09504 640.2173731 640.3397062 640.4620392 640.5843723 640.7067054 640.8290385 640.9513715 641.0737046 641.1960377 641.3183708 641.4407038 641.5630369 641.68537 641.8077031 641.9300362 642.0523692 642.1747023 642.2970354 642.4193685 642.5417015 642.6640346 642.7863677 642.9087008 643.0310338 643.1533669 643.2757 643.3980331 643.5203662 643.6426992 643.7650323 643.8873654 644.0096985 644.1320315 644.2543646 644.3766977 644.4990308 644.6213638 644.7436969 644.86603 644.9883631 645.1106962 645.2330292 645.3553623 645.4776954 645.6000285 645.7223615 645.8446946 645.9670277 646.0893608 646.2116938 646.3340269 646.45636 646.5786931 646.7010262 646.8233592 646.9456923 647.0680254 647.1903585 647.3126915 647.4350246 647.5573577 647.6796908 647.8020238 647.9243569 648.04669 648.1690231 648.2913562 648.4136892 648.5360223 648.6583554 648.7806885 648.9030215 649.0253546 649.1476877 649.2700208 649.3923538 649.5146869 649.63702 649.7593531 649.8816862 650.0040192 650.1263523 650.2486854 650.3710185 650.4933515 650.6156846 650.7380177 650.8603508 650.9826838 651.1050169 651.22735 651.3496831 651.4720162 651.5943492 651.7166823 651.8390154 651.9613485 652.0836815 652.2060146 652.3283477 652.4506808 652.5730138 652.6953469 652.81768 652.9400131 653.0623462 653.1846792 653.3070123 653.4293454 653.5516785 653.6740115 653.7963446 653.9186777 654.0410108 654.1633438 654.2856769 654.40801 654.5303431 654.6526762 654.7750092 654.8973423 655.0196754 655.1420085 655.2643415 655.3866746 655.5090077 655.6313408 655.7536738 655.8760069 655.99834 656.1206731 656.2430062 656.3653392 656.4876723 656.6100054 656.7323385 656.8546715 656.9770046 657.0993377 657.2216708 657.3440038 657.4663369 657.58867 657.7110031 657.8333362 657.9556692 658.0780023 658.2003354 658.3226685 658.4450015 658.5673346 658.6896677 658.8120008 658.9343338 659.0566669 659.179 659.3013331 659.4236662 659.5459992 659.6683323 659.7906654 659.9129985 660.0353315 660.1576646 660.2799977 660.4023308 660.5246638 660.6469969 660.76933 660.8916631 661.0139962 661.1363292 661.2586623 661.3809954 661.5033285 661.6256615 661.7479946 661.8703277 661.9926608 662.1149938 662.2373269 662.35966 662.4819931 662.6043262 662.7266592 662.8489923 662.9713254 663.0936585 663.2159915 663.3383246 663.4606577 663.5829908 663.7053238 663.8276569 663.94999 664.0723231 664.1946562 664.3169892 664.4393223 664.5616554 664.6839885 664.8063215 664.9286546 665.0509877 665.1733208 665.2956538 665.4179869 665.54032 665.6626531 665.7849862 665.9073192 666.0296523 666.1519854 666.2743185 666.3966515 666.5189846 666.6413177 666.7636508 666.8859838 667.0083169 667.13065 667.2529831 667.3753162 667.4976492 667.6199823 667.7423154 667.8646485 667.9869815 668.1093146 668.2316477 668.3539808 668.4763138 668.5986469 668.72098 668.8433131 668.9656462 669.0879792 669.2103123 669.3326454 669.4549785 669.5773115 669.6996446 669.8219777 669.9443108 670.0666438 670.1889769 670.31131 670.4336431 670.5559762 670.6783092 670.8006423 670.9229754 671.0453085 671.1676415 671.2899746 671.4123077 671.5346408 671.6569738 671.7793069 671.90164 672.0239731 672.1463062 672.2686392 672.3909723 672.5133054 672.6356385 672.7579715 672.8803046 673.0026377 673.1249708 673.2473038 673.3696369 673.49197 673.6143031 673.7366362 673.8589692 673.9813023 674.1036354 674.2259685 674.3483015 674.4706346 674.5929677 674.7153008 674.8376338 674.9599669 675.0823 675.2046331 675.3269662 675.4492992 675.5716323 675.6939654 675.8162985 675.9386315 676.0609646 676.1832977 676.3056308 676.4279638 676.5502969 676.67263 676.7949631 676.9172962 677.0396292 677.1619623 677.2842954 677.4066285 677.5289615 677.6512946 677.7736277 677.8959608 678.0182938 678.1406269 678.26296 678.3852931 678.5076262 678.6299592 678.7522923 678.8746254 678.9969585 679.1192915 679.2416246 679.3639577 679.4862908 679.6086238 679.7309569 679.85329 679.9756231 680.0979562 680.2202892 680.3426223 680.4649554 680.5872885 680.7096215 680.8319546 680.9542877 681.0766208 681.1989538 681.3212869 681.44362 681.5659531 681.6882862 681.8106192 681.9329523 682.0552854 682.1776185 682.2999515 682.4222846 682.5446177 682.6669508 682.7892838 682.9116169 683.03395 683.1562831 683.2786162 683.4009492 683.5232823 683.6456154 683.7679485 683.8902815 684.0126146 684.1349477 684.2572808 684.3796138 684.5019469 684.62428 684.7466131 684.8689462 684.9912792 685.1136123 685.2359454 685.3582785 685.4806115 685.6029446 685.7252777 685.8476108 685.9699438 686.0922769 686.21461 686.3369431 686.4592762 686.5816092 686.7039423 686.8262754 686.9486085 687.0709415 687.1932746 687.3156077 687.4379408 687.5602738 687.6826069 687.80494 687.9272731 688.0496062 688.1719392 688.2942723 688.4166054 688.5389385 688.6612715 688.7836046 688.9059377 689.0282708 689.1506038 689.2729369 689.39527 689.5176031 689.6399362 689.7622692 689.8846023 690.0069354 690.1292685 690.2516015 690.3739346 690.4962677 690.6186008 690.7409338 690.8632669 690.9856 691.1079331 691.2302662 691.3525992 691.4749323 691.5972654 691.7195985 691.8419315 691.9642646 692.0865977 692.2089308 692.3312638 692.4535969 692.57593 692.6982631 692.8205962 692.9429292 693.0652623 693.1875954 693.3099285 693.4322615 693.5545946 693.6769277 693.7992608 693.9215938 694.0439269 694.16626 694.2885931 694.4109262 694.5332592 694.6555923 694.7779254 694.9002585 695.0225915 695.1449246 695.2672577 695.3895908 695.5119238 695.6342569 695.75659 695.8789231 696.0012562 696.1235892 696.2459223 696.3682554 696.4905885 696.6129215 696.7352546 696.8575877 696.9799208 697.1022538 697.2245869 697.34692 697.4692531 697.5915862 697.7139192 697.8362523 697.9585854 698.0809185 698.2032515 698.3255846 698.4479177 698.5702508 698.6925838 698.8149169 698.93725 699.0595831 699.1819162 699.3042492 699.4265823 699.5489154 699.6712485 699.7935815 699.9159146 700.0382477 700.1605808 700.2829138 700.4052469 700.52758 700.6499131 700.7722462 700.8945792 701.0169123 701.1392454 701.2615785 701.3839115 701.5062446 701.6285777 701.7509108 701.8732438 701.9955769 702.11791 702.2402431 702.3625762 702.4849092 702.6072423 702.7295754 702.8519085 702.9742415 703.0965746 703.2189077 703.3412408 703.4635738 703.5859069 703.70824 703.8305731 703.9529062 704.0752392 704.1975723 704.3199054 704.4422385 704.5645715 704.6869046 704.8092377 704.9315708 705.0539038 705.1762369 705.29857 705.4209031 705.5432362 705.6655692 705.7879023 705.9102354 706.0325685 706.1549015 706.2772346 706.3995677 706.5219008 706.6442338 706.7665669 706.8889 707.0112331 707.1335662 707.2558992 707.3782323 707.5005654 707.6228985 707.7452315 707.8675646 707.9898977 708.1122308 708.2345638 708.3568969 708.47923 708.6015631 708.7238962 708.8462292 708.9685623 709.0908954 709.2132285 709.3355615 709.4578946 709.5802277 709.7025608 709.8248938 709.9472269 710.06956 710.1918931 710.3142262 710.4365592 710.5588923 710.6812254 710.8035585 710.9258915 711.0482246 711.1705577 711.2928908 711.4152238 711.5375569 711.65989 711.7822231 711.9045562 712.0268892 712.1492223 712.2715554 712.3938885 712.5162215 712.6385546 712.7608877 712.8832208 713.0055538 713.1278869 713.25022 713.3725531 713.4948862 713.6172192 713.7395523 713.8618854 713.9842185 714.1065515 714.2288846 714.3512177 714.4735508 714.5958838 714.7182169 714.84055 714.9628831 715.0852162 715.2075492 715.3298823 715.4522154 715.5745485 715.6968815 715.8192146 715.9415477 716.0638808 716.1862138 716.3085469 716.43088 716.5532131 716.6755462 716.7978792 716.9202123 717.0425454 717.1648785 717.2872115 717.4095446 717.5318777 717.6542108 717.7765438 717.8988769 718.02121 718.1435431 718.2658762 718.3882092 718.5105423 718.6328754 718.7552085 718.8775415 718.9998746 719.1222077 719.2445408 719.3668738 719.4892069 719.61154 719.7338731 719.8562062 719.9785392 720.1008723 720.2232054 720.3455385 720.4678715 720.5902046 720.7125377 720.8348708 720.9572038 721.0795369 721.20187 721.3242031 721.4465362 721.5688692 721.6912023 721.8135354 721.9358685 722.0582015 722.1805346 722.3028677 722.4252008 722.5475338 722.6698669 722.7922 722.9145331 723.0368662 723.1591992 723.2815323 723.4038654 723.5261985 723.6485315 723.7708646 723.8931977 724.0155308 724.1378638 724.2601969 724.38253 724.5048631 724.6271962 724.7495292 724.8718623 724.9941954 725.1165285 725.2388615 725.3611946 725.4835277 725.6058608 725.7281938 725.8505269 725.97286 726.0951931 726.2175262 726.3398592 726.4621923 726.5845254 726.7068585 726.8291915 726.9515246 727.0738577 727.1961908 727.3185238 727.4408569 727.56319 727.6855231 727.8078562 727.9301892 728.0525223 728.1748554 728.2971885 728.4195215 728.5418546 728.6641877 728.7865208 728.9088538 729.0311869 729.15352 729.2758531 729.3981862 729.5205192 729.6428523 729.7651854 729.8875185 730.0098515 730.1321846 730.2545177 730.3768508 730.4991838 730.6215169 730.74385 730.8661831 730.9885162 731.1108492 731.2331823 731.3555154 731.4778485 731.6001815 731.7225146 731.8448477 731.9671808 732.0895138 732.2118469 732.33418 732.4565131 732.5788462 732.7011792 732.8235123 732.9458454 733.0681785 733.1905115 733.3128446 733.4351777 733.5575108 733.6798438 733.8021769 733.92451 734.0468431 734.1691762 734.2915092 734.4138423 734.5361754 734.6585085 734.7808415 734.9031746 735.0255077 735.1478408 735.2701738 735.3925069 735.51484 735.6371731 735.7595062 735.8818392 736.0041723 736.1265054 736.2488385 736.3711715 736.4935046 736.6158377 736.7381708 736.8605038 736.9828369 737.10517 737.2275031 737.3498362 737.4721692 737.5945023 737.7168354 737.8391685 737.9615015 738.0838346 738.2061677 738.3285008 738.4508338 738.5731669 738.6955 738.8178331 738.9401662 739.0624992 739.1848323 739.3071654 739.4294985 739.5518315 739.6741646 739.7964977 739.9188308 740.0411638 740.1634969 740.28583 740.4081631 740.5304962 740.6528292 740.7751623 740.8974954 741.0198285 741.1421615 741.2644946 741.3868277 741.5091608 741.6314938 741.7538269 741.87616 741.9984931 742.1208262 742.2431592 742.3654923 742.4878254 742.6101585 742.7324915 742.8548246 742.9771577 743.0994908 743.2218238 743.3441569 743.46649 743.5888231 743.7111562 743.8334892 743.9558223 744.0781554 744.2004885 744.3228215 744.4451546 744.5674877 744.6898208 744.8121538 744.9344869 745.05682 745.1791531 745.3014862 745.4238192 745.5461523 745.6684854 745.7908185 745.9131515 746.0354846 746.1578177 746.2801508 746.4024838 746.5248169 746.64715 746.7694831 746.8918162 747.0141492 747.1364823 747.2588154 747.3811485 747.5034815 747.6258146 747.7481477 747.8704808 747.9928138 748.1151469 748.23748 748.3598131 748.4821462 748.6044792 748.7268123 748.8491454 748.9714785 749.0938115 749.2161446 749.3384777 749.4608108 749.5831438 749.7054769 749.82781 749.9501431 750.0724762 750.1948092 750.3171423 750.4394754 750.5618085 750.6841415 750.8064746 750.9288077 751.0511408 751.1734738 751.2958069 751.41814 751.5404731 751.6628062 751.7851392 751.9074723 752.0298054 752.1521385 752.2744715 752.3968046 752.5191377 752.6414708 752.7638038 752.8861369 753.00847 753.1308031 753.2531362 753.3754692 753.4978023 753.6201354 753.7424685 753.8648015 753.9871346 754.1094677 754.2318008 754.3541338 754.4764669 754.5988 754.7211331 754.8434662 754.9657992 755.0881323 755.2104654 755.3327985 755.4551315 755.5774646 755.6997977 755.8221308 755.9444638 756.0667969 756.18913 756.3114631 756.4337962 756.5561292 756.6784623 756.8007954 756.9231285 757.0454615 757.1677946 757.2901277 757.4124608 757.5347938 757.6571269 757.77946 757.9017931 758.0241262 758.1464592 758.2687923 758.3911254 758.5134585 758.6357915 758.7581246 758.8804577 759.0027908 759.1251238 759.2474569 759.36979 759.4921231 759.6144562 759.7367892 759.8591223 759.9814554 760.1037885 760.2261215 760.3484546 760.4707877 760.5931208 760.7154538 760.8377869 760.96012 761.0824531 761.2047862 761.3271192 761.4494523 761.5717854 761.6941185 761.8164515 761.9387846 762.0611177 762.1834508 762.3057838 762.4281169 762.55045 762.6727831 762.7951162 762.9174492 763.0397823 763.1621154 763.2844485 763.4067815 763.5291146 763.6514477 763.7737808 763.8961138 764.0184469 764.14078 764.2631131 764.3854462 764.5077792 764.6301123 764.7524454 764.8747785 764.9971115 765.1194446 765.2417777 765.3641108 765.4864438 765.6087769 765.73111 765.8534431 765.9757762 766.0981092 766.2204423 766.3427754 766.4651085 766.5874415 766.7097746 766.8321077 766.9544408 767.0767738 767.1991069 767.32144 767.4437731 767.5661062 767.6884392 767.8107723 767.9331054 768.0554385 768.1777715 768.3001046 768.4224377 768.5447708 768.6671038 768.7894369 768.91177 769.0341031 769.1564362 769.2787692 769.4011023 769.5234354 769.6457685 769.7681015 769.8904346 770.0127677 770.1351008 770.2574338 770.3797669 770.5021 770.6244331 770.7467662 770.8690992 770.9914323 771.1137654 771.2360985 771.3584315 771.4807646 771.6030977 771.7254308 771.8477638 771.9700969 772.09243 772.2147631 772.3370962 772.4594292 772.5817623 772.7040954 772.8264285 772.9487615 773.0710946 773.1934277 773.3157608 773.4380938 773.5604269 773.68276 773.8050931 773.9274262 774.0497592 774.1720923 774.2944254 774.4167585 774.5390915 774.6614246 774.7837577 774.9060908 775.0284238 775.1507569 775.27309 775.3954231 775.5177562 775.6400892 775.7624223 775.8847554 776.0070885 776.1294215 776.2517546 776.3740877 776.4964208 776.6187538 776.7410869 776.86342 776.9857531 777.1080862 777.2304192 777.3527523 777.4750854 777.5974185 777.7197515 777.8420846 777.9644177 778.0867508 778.2090838 778.3314169 778.45375 778.5760831 778.6984162 778.8207492 778.9430823 779.0654154 779.1877485 779.3100815 779.4324146 779.5547477 779.6770808 779.7994138 779.9217469 780.04408 780.1664131 780.2887462 780.4110792 780.5334123 780.6557454 780.7780785 780.9004115 781.0227446 781.1450777 781.2674108 781.3897438 781.5120769 781.63441 781.7567431 781.8790762 782.0014092 782.1237423 782.2460754 782.3684085 782.4907415 782.6130746 782.7354077 782.8577408 782.9800738 783.1024069 783.22474 783.3470731 783.4694062 783.5917392 783.7140723 783.8364054 783.9587385 784.0810715 784.2034046 784.3257377 784.4480708 784.5704038 784.6927369 784.81507 784.9374031 785.0597362 785.1820692 785.3044023 785.4267354 785.5490685 785.6714015 785.7937346 785.9160677 786.0384008 786.1607338 786.2830669 786.4054 786.5277331 786.6500662 786.7723992 786.8947323 787.0170654 787.1393985 787.2617315 787.3840646 787.5063977 787.6287308 787.7510638 787.8733969 787.99573 788.1180631 788.2403962 788.3627292 788.4850623 788.6073954 788.7297285 788.8520615 788.9743946 789.0967277 789.2190608 789.3413938 789.4637269 789.58606 789.7083931 789.8307262 789.9530592 790.0753923 790.1977254 790.3200585 790.4423915 790.5647246 790.6870577 790.8093908 790.9317238 791.0540569 791.17639 791.2987231 791.4210562 791.5433892 791.6657223 791.7880554 791.9103885 792.0327215 792.1550546 792.2773877 792.3997208 792.5220538 792.6443869 792.76672 792.8890531 793.0113862 793.1337192 793.2560523 793.3783854 793.5007185 793.6230515 793.7453846 793.8677177 793.9900508 794.1123838 794.2347169 794.35705 794.4793831 794.6017162 794.7240492 794.8463823 794.9687154 795.0910485 795.2133815 795.3357146 795.4580477 795.5803808 795.7027138 795.8250469 795.94738 796.0697131 796.1920462 796.3143792 796.4367123 796.5590454 796.6813785 796.8037115 796.9260446 797.0483777 797.1707108 797.2930438 797.4153769 797.53771 797.6600431 797.7823762 797.9047092 798.0270423 798.1493754 798.2717085 798.3940415 798.5163746 798.6387077 798.7610408 798.8833738 799.0057069 799.12804 799.2503731 799.3727062 799.4950392 799.6173723 799.7397054 799.8620385 799.9843715 800.1067046 800.2290377 800.3513708 800.4737038 800.5960369 800.71837 800.8407031 800.9630362 801.0853692 801.2077023 801.3300354 801.4523685 801.5747015 801.6970346 801.8193677 801.9417008 802.0640338 802.1863669 802.3087 802.4310331 802.5533662 802.6756992 802.7980323 802.9203654 803.0426985 803.1650315 803.2873646 803.4096977 803.5320308 803.6543638 803.7766969 803.89903 804.0213631 804.1436962 804.2660292 804.3883623 804.5106954 804.6330285 804.7553615 804.8776946 805.0000277 805.1223608 805.2446938 805.3670269 805.48936 805.6116931 805.7340262 805.8563592 805.9786923 806.1010254 806.2233585 806.3456915 806.4680246 806.5903577 806.7126908 806.8350238 806.9573569 807.07969 807.2020231 807.3243562 807.4466892 807.5690223 807.6913554 807.8136885 807.9360215 808.0583546 808.1806877 808.3030208 808.4253538 808.5476869 808.67002 808.7923531 808.9146862 809.0370192 809.1593523 809.2816854 809.4040185 809.5263515 809.6486846 809.7710177 809.8933508 810.0156838 810.1380169 810.26035 810.3826831 810.5050162 810.6273492 810.7496823 810.8720154 810.9943485 811.1166815 811.2390146 811.3613477 811.4836808 811.6060138 811.7283469 811.85068 811.9730131 812.0953462 812.2176792 812.3400123 812.4623454 812.5846785 812.7070115 812.8293446 812.9516777 813.0740108 813.1963438 813.3186769 813.44101 813.5633431 813.6856762 813.8080092 813.9303423 814.0526754 814.1750085 814.2973415 814.4196746 814.5420077 814.6643408 814.7866738 814.9090069 815.03134 815.1536731 815.2760062 815.3983392 815.5206723 815.6430054 815.7653385 815.8876715 816.0100046 816.1323377 816.2546708 816.3770038 816.4993369 816.62167 816.7440031 816.8663362 816.9886692 817.1110023 817.2333354 817.3556685 817.4780015 817.6003346 817.7226677 817.8450008 817.9673338 818.0896669 818.212 818.3343331 818.4566662 818.5789992 818.7013323 818.8236654 818.9459985 819.0683315 819.1906646 819.3129977 819.4353308 819.5576638 819.6799969 819.80233 819.9246631 820.0469962 820.1693292 820.2916623 820.4139954 820.5363285 820.6586615 820.7809946 820.9033277 821.0256608 821.1479938 821.2703269 821.39266 821.5149931 821.6373262 821.7596592 821.8819923 822.0043254 822.1266585 822.2489915 822.3713246 822.4936577 822.6159908 822.7383238 822.8606569 822.98299 823.1053231 823.2276562 823.3499892 823.4723223 823.5946554 823.7169885 823.8393215 823.9616546 824.0839877 824.2063208 824.3286538 824.4509869 824.57332 824.6956531 824.8179862 824.9403192 825.0626523 825.1849854 825.3073185 825.4296515 825.5519846 825.6743177 825.7966508 825.9189838 826.0413169 826.16365 826.2859831 826.4083162 826.5306492 826.6529823 826.7753154 826.8976485 827.0199815 827.1423146 827.2646477 827.3869808 827.5093138 827.6316469 827.75398 827.8763131 827.9986462 828.1209792 828.2433123 828.3656454 828.4879785 828.6103115 828.7326446 828.8549777 828.9773108 829.0996438 829.2219769 829.34431 829.4666431 829.5889762 829.7113092 829.8336423 829.9559754 830.0783085 830.2006415 830.3229746 830.4453077 830.5676408 830.6899738 830.8123069 830.93464 831.0569731 831.1793062 831.3016392 831.4239723 831.5463054 831.6686385 831.7909715 831.9133046 832.0356377 832.1579708 832.2803038 832.4026369 832.52497 832.6473031 832.7696362 832.8919692 833.0143023 833.1366354 833.2589685 833.3813015 833.5036346 833.6259677 833.7483008 833.8706338 833.9929669 834.1153 834.2376331 834.3599662 834.4822992 834.6046323 834.7269654 834.8492985 834.9716315 835.0939646 835.2162977 835.3386308 835.4609638 835.5832969 835.70563 835.8279631 835.9502962 836.0726292 836.1949623 836.3172954 836.4396285 836.5619615 836.6842946 836.8066277 836.9289608 837.0512938 837.1736269 837.29596 837.4182931 837.5406262 837.6629592 837.7852923 837.9076254 838.0299585 838.1522915 838.2746246 838.3969577 838.5192908 838.6416238 838.7639569 838.88629 839.0086231 839.1309562 839.2532892 839.3756223 839.4979554 839.6202885 839.7426215 839.8649546 839.9872877 840.1096208 840.2319538 840.3542869 840.47662 840.5989531 840.7212862 840.8436192 840.9659523 841.0882854 841.2106185 841.3329515 841.4552846 841.5776177 841.6999508 841.8222838 841.9446169 842.06695 842.1892831 842.3116162 842.4339492 842.5562823 842.6786154 842.8009485 842.9232815 843.0456146 843.1679477 843.2902808 843.4126138 843.5349469 843.65728 843.7796131 843.9019462 844.0242792 844.1466123 844.2689454 844.3912785 844.5136115 844.6359446 844.7582777 844.8806108 845.0029438 845.1252769 845.24761 845.3699431 845.4922762 845.6146092 845.7369423 845.8592754 845.9816085 846.1039415 846.2262746 846.3486077 846.4709408 846.5932738 846.7156069 846.83794 846.9602731 847.0826062 847.2049392 847.3272723 847.4496054 847.5719385 847.6942715 847.8166046 847.9389377 848.0612708 848.1836038 848.3059369 848.42827 848.5506031 848.6729362 848.7952692 848.9176023 849.0399354 849.1622685 849.2846015 849.4069346 849.5292677 849.6516008 849.7739338 849.8962669 850.0186 850.1409331 850.2632662 850.3855992 850.5079323 850.6302654 850.7525985 850.8749315 850.9972646 851.1195977 851.2419308 851.3642638 851.4865969 851.60893 851.7312631 851.8535962 851.9759292 852.0982623 852.2205954 852.3429285 852.4652615 852.5875946 852.7099277 852.8322608 852.9545938 853.0769269 853.19926 853.3215931 853.4439262 853.5662592 853.6885923 853.8109254 853.9332585 854.0555915 854.1779246 854.3002577 854.4225908 854.5449238 854.6672569 854.78959 854.9119231 855.0342562 855.1565892 855.2789223 855.4012554 855.5235885 855.6459215 855.7682546 855.8905877 856.0129208 856.1352538 856.2575869 856.37992 856.5022531 856.6245862 856.7469192 856.8692523 856.9915854 857.1139185 857.2362515 857.3585846 857.4809177 857.6032508 857.7255838 857.8479169 857.97025 858.0925831 858.2149162 858.3372492 858.4595823 858.5819154 858.7042485 858.8265815 858.9489146 859.0712477 859.1935808 859.3159138 859.4382469 859.56058 859.6829131 859.8052462 859.9275792 860.0499123 860.1722454 860.2945785 860.4169115 860.5392446 860.6615777 860.7839108 860.9062438 861.0285769 861.15091 861.2732431 861.3955762 861.5179092 861.6402423 861.7625754 861.8849085 862.0072415 862.1295746 862.2519077 862.3742408 862.4965738 862.6189069 862.74124 862.8635731 862.9859062 863.1082392 863.2305723 863.3529054 863.4752385 863.5975715 863.7199046 863.8422377 863.9645708 864.0869038 864.2092369 864.33157 864.4539031 864.5762362 864.6985692 864.8209023 864.9432354 865.0655685 865.1879015 865.3102346 865.4325677 865.5549008 865.6772338 865.7995669 865.9219 866.0442331 866.1665662 866.2888992 866.4112323 866.5335654 866.6558985 866.7782315 866.9005646 867.0228977 867.1452308 867.2675638 867.3898969 867.51223 867.6345631 867.7568962 867.8792292 868.0015623 868.1238954 868.2462285 868.3685615 868.4908946 868.6132277 868.7355608 868.8578938 868.9802269 869.10256 869.2248931 869.3472262 869.4695592 869.5918923 869.7142254 869.8365585 869.9588915 870.0812246 870.2035577 870.3258908 870.4482238 870.5705569 870.69289 870.8152231 870.9375562 871.0598892 871.1822223 871.3045554 871.4268885 871.5492215 871.6715546 871.7938877 871.9162208 872.0385538 872.1608869 872.28322 872.4055531 872.5278862 872.6502192 872.7725523 872.8948854 873.0172185 873.1395515 873.2618846 873.3842177 873.5065508 873.6288838 873.7512169 873.87355 873.9958831 874.1182162 874.2405492 874.3628823 874.4852154 874.6075485 874.7298815 874.8522146 874.9745477 875.0968808 875.2192138 875.3415469 875.46388 875.5862131 875.7085462 875.8308792 875.9532123 876.0755454 876.1978785 876.3202115 876.4425446 876.5648777 876.6872108 876.8095438 876.9318769 877.05421 877.1765431 877.2988762 877.4212092 877.5435423 877.6658754 877.7882085 877.9105415 878.0328746 878.1552077 878.2775408 878.3998738 878.5222069 878.64454 878.7668731 878.8892062 879.0115392 879.1338723 879.2562054 879.3785385 879.5008715 879.6232046 879.7455377 879.8678708 879.9902038 880.1125369 880.23487 880.3572031 880.4795362 880.6018692 880.7242023 880.8465354 880.9688685 881.0912015 881.2135346 881.3358677 881.4582008 881.5805338 881.7028669 881.8252 881.9475331 882.0698662 882.1921992 882.3145323 882.4368654 882.5591985 882.6815315 882.8038646 882.9261977 883.0485308 883.1708638 883.2931969 883.41553 883.5378631 883.6601962 883.7825292 883.9048623 884.0271954 884.1495285 884.2718615 884.3941946 884.5165277 884.6388608 884.7611938 884.8835269 885.00586 885.1281931 885.2505262 885.3728592 885.4951923 885.6175254 885.7398585 885.8621915 885.9845246 886.1068577 886.2291908 886.3515238 886.4738569 886.59619 886.7185231 886.8408562 886.9631892 887.0855223 887.2078554 887.3301885 887.4525215 887.5748546 887.6971877 887.8195208 887.9418538 888.0641869 888.18652 888.3088531 888.4311862 888.5535192 888.6758523 888.7981854 888.9205185 889.0428515 889.1651846 889.2875177 889.4098508 889.5321838 889.6545169 889.77685 889.8991831 890.0215162 890.1438492 890.2661823 890.3885154 890.5108485 890.6331815 890.7555146 890.8778477 891.0001808 891.1225138 891.2448469 891.36718 891.4895131 891.6118462 891.7341792 891.8565123 891.9788454 892.1011785 892.2235115 892.3458446 892.4681777 892.5905108 892.7128438 892.8351769 892.95751 893.0798431 893.2021762 893.3245092 893.4468423 893.5691754 893.6915085 893.8138415 893.9361746 894.0585077 894.1808408 894.3031738 894.4255069 894.54784 894.6701731 894.7925062 894.9148392 895.0371723 895.1595054 895.2818385 895.4041715 895.5265046 895.6488377 895.7711708 895.8935038 896.0158369 896.13817 896.2605031 896.3828362 896.5051692 896.6275023 896.7498354 896.8721685 896.9945015 897.1168346 897.2391677 897.3615008 897.4838338 897.6061669 897.7285 897.8508331 897.9731662 898.0954992 898.2178323 898.3401654 898.4624985 898.5848315 898.7071646 898.8294977 898.9518308 899.0741638 899.1964969 899.31883 899.4411631 899.5634962 899.6858292 899.8081623 899.9304954 900.0528285 900.1751615 900.2974946 900.4198277 900.5421608 900.6644938 900.7868269 900.90916 901.0314931 901.1538262 901.2761592 901.3984923 901.5208254 901.6431585 901.7654915 901.8878246 902.0101577 902.1324908 902.2548238 902.3771569 902.49949 902.6218231 902.7441562 902.8664892 902.9888223 903.1111554 903.2334885 903.3558215 903.4781546 903.6004877 903.7228208 903.8451538 903.9674869 904.08982 904.2121531 904.3344862 904.4568192 904.5791523 904.7014854 904.8238185 904.9461515 905.0684846 905.1908177 905.3131508 905.4354838 905.5578169 905.68015 905.8024831 905.9248162 906.0471492 906.1694823 906.2918154 906.4141485 906.5364815 906.6588146 906.7811477 906.9034808 907.0258138 907.1481469 907.27048 907.3928131 907.5151462 907.6374792 907.7598123 907.8821454 908.0044785 908.1268115 908.2491446 908.3714777 908.4938108 908.6161438 908.7384769 908.86081 908.9831431 909.1054762 909.2278092 909.3501423 909.4724754 909.5948085 909.7171415 909.8394746 909.9618077 910.0841408 910.2064738 910.3288069 910.45114 910.5734731 910.6958062 910.8181392 910.9404723 911.0628054 911.1851385 911.3074715 911.4298046 911.5521377 911.6744708 911.7968038 911.9191369 912.04147 912.1638031 912.2861362 912.4084692 912.5308023 912.6531354 912.7754685 912.8978015 913.0201346 913.1424677 913.2648008 913.3871338 913.5094669 913.6318 913.7541331 913.8764662 913.9987992 914.1211323 914.2434654 914.3657985 914.4881315 914.6104646 914.7327977 914.8551308 914.9774638 915.0997969 915.22213 915.3444631 915.4667962 915.5891292 915.7114623 915.8337954 915.9561285 916.0784615 916.2007946 916.3231277 916.4454608 916.5677938 916.6901269 916.81246 916.9347931 917.0571262 917.1794592 917.3017923 917.4241254 917.5464585 917.6687915 917.7911246 917.9134577 918.0357908 918.1581238 918.2804569 918.40279 918.5251231 918.6474562 918.7697892 918.8921223 919.0144554 919.1367885 919.2591215 919.3814546 919.5037877 919.6261208 919.7484538 919.8707869 919.99312 920.1154531 920.2377862 920.3601192 920.4824523 920.6047854 920.7271185 920.8494515 920.9717846 921.0941177 921.2164508 921.3387838 921.4611169 921.58345 921.7057831 921.8281162 921.9504492 922.0727823 922.1951154 922.3174485 922.4397815 922.5621146 922.6844477 922.8067808 922.9291138 923.0514469 923.17378 923.2961131 923.4184462 923.5407792 923.6631123 923.7854454 923.9077785 924.0301115 924.1524446 924.2747777 924.3971108 924.5194438 924.6417769 924.76411 924.8864431 925.0087762 925.1311092 925.2534423 925.3757754 925.4981085 925.6204415 925.7427746 925.8651077 925.9874408 926.1097738 926.2321069 926.35444 926.4767731 926.5991062 926.7214392 926.8437723 926.9661054 927.0884385 927.2107715 927.3331046 927.4554377 927.5777708 927.7001038 927.8224369 927.94477 928.0671031 928.1894362 928.3117692 928.4341023 928.5564354 928.6787685 928.8011015 928.9234346 929.0457677 929.1681008 929.2904338 929.4127669 929.5351 929.6574331 929.7797662 929.9020992 930.0244323 930.1467654 930.2690985 930.3914315 930.5137646 930.6360977 930.7584308 930.8807638 931.0030969 931.12543 931.2477631 931.3700962 931.4924292 931.6147623 931.7370954 931.8594285 931.9817615 932.1040946 932.2264277 932.3487608 932.4710938 932.5934269 932.71576 932.8380931 932.9604262 933.0827592 933.2050923 933.3274254 933.4497585 933.5720915 933.6944246 933.8167577 933.9390908 934.0614238 934.1837569 934.30609 934.4284231 934.5507562 934.6730892 934.7954223 934.9177554 935.0400885 935.1624215 935.2847546 935.4070877 935.5294208 935.6517538 935.7740869 935.89642 936.0187531 936.1410862 936.2634192 936.3857523 936.5080854 936.6304185 936.7527515 936.8750846 936.9974177 937.1197508 937.2420838 937.3644169 937.48675 937.6090831 937.7314162 937.8537492 937.9760823 938.0984154 938.2207485 938.3430815 938.4654146 938.5877477 938.7100808 938.8324138 938.9547469 939.07708 939.1994131 939.3217462 939.4440792 939.5664123 939.6887454 939.8110785 939.9334115 940.0557446 940.1780777 940.3004108 940.4227438 940.5450769 940.66741 940.7897431 940.9120762 941.0344092 941.1567423 941.2790754 941.4014085 941.5237415 941.6460746 941.7684077 941.8907408 942.0130738 942.1354069 942.25774 942.3800731 942.5024062 942.6247392 942.7470723 942.8694054 942.9917385 943.1140715 943.2364046 943.3587377 943.4810708 943.6034038 943.7257369 943.84807 943.9704031 944.0927362 944.2150692 944.3374023 944.4597354 944.5820685 944.7044015 944.8267346 944.9490677 945.0714008 945.1937338 945.3160669 945.4384 945.5607331 945.6830662 945.8053992 945.9277323 946.0500654 946.1723985 946.2947315 946.4170646 946.5393977 946.6617308 946.7840638 946.9063969 947.02873 947.1510631 947.2733962 947.3957292 947.5180623 947.6403954 947.7627285 947.8850615 948.0073946 948.1297277 948.2520608 948.3743938 948.4967269 948.61906 948.7413931 948.8637262 948.9860592 949.1083923 949.2307254 949.3530585 949.4753915 949.5977246 949.7200577 949.8423908 949.9647238 950.0870569 950.20939 950.3317231 950.4540562 950.5763892 950.6987223 950.8210554 950.9433885 951.0657215 951.1880546 951.3103877 951.4327208 951.5550538 951.6773869 951.79972 951.9220531 952.0443862 952.1667192 952.2890523 952.4113854 952.5337185 952.6560515 952.7783846 952.9007177 953.0230508 953.1453838 953.2677169 953.39005 953.5123831 953.6347162 953.7570492 953.8793823 954.0017154 954.1240485 954.2463815 954.3687146 954.4910477 954.6133808 954.7357138 954.8580469 954.98038 955.1027131 955.2250462 955.3473792 955.4697123 955.5920454 955.7143785 955.8367115 955.9590446 956.0813777 956.2037108 956.3260438 956.4483769 956.57071 956.6930431 956.8153762 956.9377092 957.0600423 957.1823754 957.3047085 957.4270415 957.5493746 957.6717077 957.7940408 957.9163738 958.0387069 958.16104 958.2833731 958.4057062 958.5280392 958.6503723 958.7727054 958.8950385 959.0173715 959.1397046 959.2620377 959.3843708 959.5067038 959.6290369 959.75137 959.8737031 959.9960362 960.1183692 960.2407023 960.3630354 960.4853685 960.6077015 960.7300346 960.8523677 960.9747008 961.0970338 961.2193669 961.3417 961.4640331 961.5863662 961.7086992 961.8310323 961.9533654 962.0756985 962.1980315 962.3203646 962.4426977 962.5650308 962.6873638 962.8096969 962.93203 963.0543631 963.1766962 963.2990292 963.4213623 963.5436954 963.6660285 963.7883615 963.9106946 964.0330277 964.1553608 964.2776938 964.4000269 964.52236 964.6446931 964.7670262 964.8893592 965.0116923 965.1340254 965.2563585 965.3786915 965.5010246 965.6233577 965.7456908 965.8680238 965.9903569 966.11269 966.2350231 966.3573562 966.4796892 966.6020223 966.7243554 966.8466885 966.9690215 967.0913546 967.2136877 967.3360208 967.4583538 967.5806869 967.70302 967.8253531 967.9476862 968.0700192 968.1923523 968.3146854 968.4370185 968.5593515 968.6816846 968.8040177 968.9263508 969.0486838 969.1710169 969.29335 969.4156831 969.5380162 969.6603492 969.7826823 969.9050154 970.0273485 970.1496815 970.2720146 970.3943477 970.5166808 970.6390138 970.7613469 970.88368 971.0060131 971.1283462 971.2506792 971.3730123 971.4953454 971.6176785 971.7400115 971.8623446 971.9846777 972.1070108 972.2293438 972.3516769 972.47401 972.5963431 972.7186762 972.8410092 972.9633423 973.0856754 973.2080085 973.3303415 973.4526746 973.5750077 973.6973408 973.8196738 973.9420069 974.06434 974.1866731 974.3090062 974.4313392 974.5536723 974.6760054 974.7983385 974.9206715 975.0430046 975.1653377 975.2876708 975.4100038 975.5323369 975.65467 975.7770031 975.8993362 976.0216692 976.1440023 976.2663354 976.3886685 976.5110015 976.6333346 976.7556677 976.8780008 977.0003338 977.1226669 977.245 977.3673331 977.4896662 977.6119992 977.7343323 977.8566654 977.9789985 978.1013315 978.2236646 978.3459977 978.4683308 978.5906638 978.7129969 978.83533 978.9576631 979.0799962 979.2023292 979.3246623 979.4469954 979.5693285 979.6916615 979.8139946 979.9363277 980.0586608 980.1809938 980.3033269 980.42566 980.5479931 980.6703262 980.7926592 980.9149923 981.0373254 981.1596585 981.2819915 981.4043246 981.5266577 981.6489908 981.7713238 981.8936569 982.01599 982.1383231 982.2606562 982.3829892 982.5053223 982.6276554 982.7499885 982.8723215 982.9946546 983.1169877 983.2393208 983.3616538 983.4839869 983.60632 983.7286531 983.8509862 983.9733192 984.0956523 984.2179854 984.3403185 984.4626515 984.5849846 984.7073177 984.8296508 984.9519838 985.0743169 985.19665 985.3189831 985.4413162 985.5636492 985.6859823 985.8083154 985.9306485 986.0529815 986.1753146 986.2976477 986.4199808 986.5423138 986.6646469 986.78698 986.9093131 987.0316462 987.1539792 987.2763123 987.3986454 987.5209785 987.6433115 987.7656446 987.8879777 988.0103108 988.1326438 988.2549769 988.37731 988.4996431 988.6219762 988.7443092 988.8666423 988.9889754 989.1113085 989.2336415 989.3559746 989.4783077 989.6006408 989.7229738 989.8453069 989.96764 990.0899731 990.2123062 990.3346392 990.4569723 990.5793054 990.7016385 990.8239715 990.9463046 991.0686377 991.1909708 991.3133038 991.4356369 991.55797 991.6803031 991.8026362 991.9249692 992.0473023 992.1696354 992.2919685 992.4143015 992.5366346 992.6589677 992.7813008 992.9036338 993.0259669 993.1483 993.2706331 993.3929662 993.5152992 993.6376323 993.7599654 993.8822985 994.0046315 994.1269646 994.2492977 994.3716308 994.4939638 994.6162969 994.73863 994.8609631 994.9832962 995.1056292 995.2279623 995.3502954 995.4726285 995.5949615 995.7172946 995.8396277 995.9619608 996.0842938 996.2066269 996.32896 996.4512931 996.5736262 996.6959592 996.8182923 996.9406254 997.0629585 997.1852915 997.3076246 997.4299577 997.5522908 997.6746238 997.7969569 997.91929 998.0416231 998.1639562 998.2862892 998.4086223 998.5309554 998.6532885 998.7756215 998.8979546 999.0202877 999.1426208 999.2649538 999.3872869 999.50962 999.6319531 999.7542862 999.8766192 999.9989523 1000.121285 1000.243618 1000.365952 1000.488285 1000.610618 1000.732951 1000.855284 1000.977617 1001.09995 1001.222283 1001.344616 1001.466949 1001.589282 1001.711615 1001.833948 1001.956282 1002.078615 1002.200948 1002.323281 1002.445614 1002.567947 1002.69028 1002.812613 1002.934946 1003.057279 1003.179612 1003.301945 1003.424278 1003.546612 1003.668945 1003.791278 1003.913611 1004.035944 1004.158277 1004.28061 1004.402943 1004.525276 1004.647609 1004.769942 1004.892275 1005.014608 1005.136942 1005.259275 1005.381608 1005.503941 1005.626274 1005.748607 1005.87094 1005.993273 1006.115606 1006.237939 1006.360272 1006.482605 1006.604938 1006.727272 1006.849605 1006.971938 1007.094271 1007.216604 1007.338937 1007.46127 1007.583603 1007.705936 1007.828269 1007.950602 1008.072935 1008.195268 1008.317602 1008.439935 1008.562268 1008.684601 1008.806934 1008.929267 1009.0516 1009.173933 1009.296266 1009.418599 1009.540932 1009.663265 1009.785598 1009.907932 1010.030265 1010.152598 1010.274931 1010.397264 1010.519597 1010.64193 1010.764263 1010.886596 1011.008929 1011.131262 1011.253595 1011.375928 1011.498262 1011.620595 1011.742928 1011.865261 1011.987594 1012.109927 1012.23226 1012.354593 1012.476926 1012.599259 1012.721592 1012.843925 1012.966258 1013.088592 1013.210925 1013.333258 1013.455591 1013.577924 1013.700257 1013.82259 1013.944923 1014.067256 1014.189589 1014.311922 1014.434255 1014.556588 1014.678922 1014.801255 1014.923588 1015.045921 1015.168254 1015.290587 1015.41292 1015.535253 1015.657586 1015.779919 1015.902252 1016.024585 1016.146918 1016.269252 1016.391585 1016.513918 1016.636251 1016.758584 1016.880917 1017.00325 1017.125583 1017.247916 1017.370249 1017.492582 1017.614915 1017.737248 1017.859582 1017.981915 1018.104248 1018.226581 1018.348914 1018.471247 1018.59358 1018.715913 1018.838246 1018.960579 1019.082912 1019.205245 1019.327578 1019.449912 1019.572245 1019.694578 1019.816911 1019.939244 1020.061577 1020.18391 1020.306243 1020.428576 1020.550909 1020.673242 1020.795575 1020.917908 1021.040242 1021.162575 1021.284908 1021.407241 1021.529574 1021.651907 1021.77424 1021.896573 1022.018906 1022.141239 1022.263572 1022.385905 1022.508238 1022.630572 1022.752905 1022.875238 1022.997571 1023.119904 1023.242237 1023.36457 1023.486903 1023.609236 1023.731569 1023.853902 1023.976235 1024.098568 1024.220902 1024.343235 1024.465568 1024.587901 1024.710234 1024.832567 1024.9549 1025.077233 1025.199566 1025.321899 1025.444232 1025.566565 1025.688898 1025.811232 1025.933565 1026.055898 1026.178231 1026.300564 1026.422897 1026.54523 1026.667563 1026.789896 1026.912229 1027.034562 1027.156895 1027.279228 1027.401562 1027.523895 1027.646228 1027.768561 1027.890894 1028.013227 1028.13556 1028.257893 1028.380226 1028.502559 1028.624892 1028.747225 1028.869558 1028.991892 1029.114225 1029.236558 1029.358891 1029.481224 1029.603557 1029.72589 1029.848223 1029.970556 1030.092889 1030.215222 1030.337555 1030.459888 1030.582222 1030.704555 1030.826888 1030.949221 1031.071554 1031.193887 1031.31622 1031.438553 1031.560886 1031.683219 1031.805552 1031.927885 1032.050218 1032.172552 1032.294885 1032.417218 1032.539551 1032.661884 1032.784217 1032.90655 1033.028883 1033.151216 1033.273549 1033.395882 1033.518215 1033.640548 1033.762882 1033.885215 1034.007548 1034.129881 1034.252214 1034.374547 1034.49688 1034.619213 1034.741546 1034.863879 1034.986212 1035.108545 1035.230878 1035.353212 1035.475545 1035.597878 1035.720211 1035.842544 1035.964877 1036.08721 1036.209543 1036.331876 1036.454209 1036.576542 1036.698875 1036.821208 1036.943542 1037.065875 1037.188208 1037.310541 1037.432874 1037.555207 1037.67754 1037.799873 1037.922206 1038.044539 1038.166872 1038.289205 1038.411538 1038.533872 1038.656205 1038.778538 1038.900871 1039.023204 1039.145537 1039.26787 1039.390203 1039.512536 1039.634869 1039.757202 1039.879535 1040.001868 1040.124202 1040.246535 1040.368868 1040.491201 1040.613534 1040.735867 1040.8582 1040.980533 1041.102866 1041.225199 1041.347532 1041.469865 1041.592198 1041.714532 1041.836865 1041.959198 1042.081531 1042.203864 1042.326197 1042.44853 1042.570863 1042.693196 1042.815529 1042.937862 1043.060195 1043.182528 1043.304862 1043.427195 1043.549528 1043.671861 1043.794194 1043.916527 1044.03886 1044.161193 1044.283526 1044.405859 1044.528192 1044.650525 1044.772858 1044.895192 1045.017525 1045.139858 1045.262191 1045.384524 1045.506857 1045.62919 1045.751523 1045.873856 1045.996189 1046.118522 1046.240855 1046.363188 1046.485522 1046.607855 1046.730188 1046.852521 1046.974854 1047.097187 1047.21952 1047.341853 1047.464186 1047.586519 1047.708852 1047.831185 1047.953518 1048.075852 1048.198185 1048.320518 1048.442851 1048.565184 1048.687517 1048.80985 1048.932183 1049.054516 1049.176849 1049.299182 1049.421515 1049.543848 1049.666182 1049.788515 1049.910848 1050.033181 1050.155514 1050.277847 1050.40018 1050.522513 1050.644846 1050.767179 1050.889512 1051.011845 1051.134178 1051.256512 1051.378845 1051.501178 1051.623511 1051.745844 1051.868177 1051.99051 1052.112843 1052.235176 1052.357509 1052.479842 1052.602175 1052.724508 1052.846842 1052.969175 1053.091508 1053.213841 1053.336174 1053.458507 1053.58084 1053.703173 1053.825506 1053.947839 1054.070172 1054.192505 1054.314838 1054.437172 1054.559505 1054.681838 1054.804171 1054.926504 1055.048837 1055.17117 1055.293503 1055.415836 1055.538169 1055.660502 1055.782835 1055.905168 1056.027502 1056.149835 1056.272168 1056.394501 1056.516834 1056.639167 1056.7615 1056.883833 1057.006166 1057.128499 1057.250832 1057.373165 1057.495498 1057.617832 1057.740165 1057.862498 1057.984831 1058.107164 1058.229497 1058.35183 1058.474163 1058.596496 1058.718829 1058.841162 1058.963495 1059.085828 1059.208162 1059.330495 1059.452828 1059.575161 1059.697494 1059.819827 1059.94216 1060.064493 1060.186826 1060.309159 1060.431492 1060.553825 1060.676158 1060.798492 1060.920825 1061.043158 1061.165491 1061.287824 1061.410157 1061.53249 1061.654823 1061.777156 1061.899489 1062.021822 1062.144155 1062.266488 1062.388822 1062.511155 1062.633488 1062.755821 1062.878154 1063.000487 1063.12282 1063.245153 1063.367486 1063.489819 1063.612152 1063.734485 1063.856818 1063.979152 1064.101485 1064.223818 1064.346151 1064.468484 1064.590817 1064.71315 1064.835483 1064.957816 1065.080149 1065.202482 1065.324815 1065.447148 1065.569482 1065.691815 1065.814148 1065.936481 1066.058814 1066.181147 1066.30348 1066.425813 1066.548146 1066.670479 1066.792812 1066.915145 1067.037478 1067.159812 1067.282145 1067.404478 1067.526811 1067.649144 1067.771477 1067.89381 1068.016143 1068.138476 1068.260809 1068.383142 1068.505475 1068.627808 1068.750142 1068.872475 1068.994808 1069.117141 1069.239474 1069.361807 1069.48414 1069.606473 1069.728806 1069.851139 1069.973472 1070.095805 1070.218138 1070.340472 1070.462805 1070.585138 1070.707471 1070.829804 1070.952137 1071.07447 1071.196803 1071.319136 1071.441469 1071.563802 1071.686135 1071.808468 1071.930802 1072.053135 1072.175468 1072.297801 1072.420134 1072.542467 1072.6648 1072.787133 1072.909466 1073.031799 1073.154132 1073.276465 1073.398798 1073.521132 1073.643465 1073.765798 1073.888131 1074.010464 1074.132797 1074.25513 1074.377463 1074.499796 1074.622129 1074.744462 1074.866795 1074.989128 1075.111462 1075.233795 1075.356128 1075.478461 1075.600794 1075.723127 1075.84546 1075.967793 1076.090126 1076.212459 1076.334792 1076.457125 1076.579458 1076.701792 1076.824125 1076.946458 1077.068791 1077.191124 1077.313457 1077.43579 1077.558123 1077.680456 1077.802789 1077.925122 1078.047455 1078.169788 1078.292122 1078.414455 1078.536788 1078.659121 1078.781454 1078.903787 1079.02612 1079.148453 1079.270786 1079.393119 1079.515452 1079.637785 1079.760118 1079.882452 1080.004785 1080.127118 1080.249451 1080.371784 1080.494117 1080.61645 1080.738783 1080.861116 1080.983449 1081.105782 1081.228115 1081.350448 1081.472782 1081.595115 1081.717448 1081.839781 1081.962114 1082.084447 1082.20678 1082.329113 1082.451446 1082.573779 1082.696112 1082.818445 1082.940778 1083.063112 1083.185445 1083.307778 1083.430111 1083.552444 1083.674777 1083.79711 1083.919443 1084.041776 1084.164109 1084.286442 1084.408775 1084.531108 1084.653442 1084.775775 1084.898108 1085.020441 1085.142774 1085.265107 1085.38744 1085.509773 1085.632106 1085.754439 1085.876772 1085.999105 1086.121438 1086.243772 1086.366105 1086.488438 1086.610771 1086.733104 1086.855437 1086.97777 1087.100103 1087.222436 1087.344769 1087.467102 1087.589435 1087.711768 1087.834102 1087.956435 1088.078768 1088.201101 1088.323434 1088.445767 1088.5681 1088.690433 1088.812766 1088.935099 1089.057432 1089.179765 1089.302098 1089.424432 1089.546765 1089.669098 1089.791431 1089.913764 1090.036097 1090.15843 1090.280763 1090.403096 1090.525429 1090.647762 1090.770095 1090.892428 1091.014762 1091.137095 1091.259428 1091.381761 1091.504094 1091.626427 1091.74876 1091.871093 1091.993426 1092.115759 1092.238092 1092.360425 1092.482758 1092.605092 1092.727425 1092.849758 1092.972091 1093.094424 1093.216757 1093.33909 1093.461423 1093.583756 1093.706089 1093.828422 1093.950755 1094.073088 1094.195422 1094.317755 1094.440088 1094.562421 1094.684754 1094.807087 1094.92942 1095.051753 1095.174086 1095.296419 1095.418752 1095.541085 1095.663418 1095.785752 1095.908085 1096.030418 1096.152751 1096.275084 1096.397417 1096.51975 1096.642083 1096.764416 1096.886749 1097.009082 1097.131415 1097.253748 1097.376082 1097.498415 1097.620748 1097.743081 1097.865414 1097.987747 1098.11008 1098.232413 1098.354746 1098.477079 1098.599412 1098.721745 1098.844078 1098.966412 1099.088745 1099.211078 1099.333411 1099.455744 1099.578077 1099.70041 1099.822743 1099.945076 1100.067409 1100.189742 1100.312075 1100.434408 1100.556742 1100.679075 1100.801408 1100.923741 1101.046074 1101.168407 1101.29074 1101.413073 1101.535406 1101.657739 1101.780072 1101.902405 1102.024738 1102.147072 1102.269405 1102.391738 1102.514071 1102.636404 1102.758737 1102.88107 1103.003403 1103.125736 1103.248069 1103.370402 1103.492735 1103.615068 1103.737402 1103.859735 1103.982068 1104.104401 1104.226734 1104.349067 1104.4714 1104.593733 1104.716066 1104.838399 1104.960732 1105.083065 1105.205398 1105.327732 1105.450065 1105.572398 1105.694731 1105.817064 1105.939397 1106.06173 1106.184063 1106.306396 1106.428729 1106.551062 1106.673395 1106.795728 1106.918062 1107.040395 1107.162728 1107.285061 1107.407394 1107.529727 1107.65206 1107.774393 1107.896726 1108.019059 1108.141392 1108.263725 1108.386058 1108.508392 1108.630725 1108.753058 1108.875391 1108.997724 1109.120057 1109.24239 1109.364723 1109.487056 1109.609389 1109.731722 1109.854055 1109.976388 1110.098722 1110.221055 1110.343388 1110.465721 1110.588054 1110.710387 1110.83272 1110.955053 1111.077386 1111.199719 1111.322052 1111.444385 1111.566718 1111.689052 1111.811385 1111.933718 1112.056051 1112.178384 1112.300717 1112.42305 1112.545383 1112.667716 1112.790049 1112.912382 1113.034715 1113.157048 1113.279382 1113.401715 1113.524048 1113.646381 1113.768714 1113.891047 1114.01338 1114.135713 1114.258046 1114.380379 1114.502712 1114.625045 1114.747378 1114.869712 1114.992045 1115.114378 1115.236711 1115.359044 1115.481377 1115.60371 1115.726043 1115.848376 1115.970709 1116.093042 1116.215375 1116.337708 1116.460042 1116.582375 1116.704708 1116.827041 1116.949374 1117.071707 1117.19404 1117.316373 1117.438706 1117.561039 1117.683372 1117.805705 1117.928038 1118.050372 1118.172705 1118.295038 1118.417371 1118.539704 1118.662037 1118.78437 1118.906703 1119.029036 1119.151369 1119.273702 1119.396035 1119.518368 1119.640702 1119.763035 1119.885368 1120.007701 1120.130034 1120.252367 1120.3747 1120.497033 1120.619366 1120.741699 1120.864032 1120.986365 1121.108698 1121.231032 1121.353365 1121.475698 1121.598031 1121.720364 1121.842697 1121.96503 1122.087363 1122.209696 1122.332029 1122.454362 1122.576695 1122.699028 1122.821362 1122.943695 1123.066028 1123.188361 1123.310694 1123.433027 1123.55536 1123.677693 1123.800026 1123.922359 1124.044692 1124.167025 1124.289358 1124.411692 1124.534025 1124.656358 1124.778691 1124.901024 1125.023357 1125.14569 1125.268023 1125.390356 1125.512689 1125.635022 1125.757355 1125.879688 1126.002022 1126.124355 1126.246688 1126.369021 1126.491354 1126.613687 1126.73602 1126.858353 1126.980686 1127.103019 1127.225352 1127.347685 1127.470018 1127.592352 1127.714685 1127.837018 1127.959351 1128.081684 1128.204017 1128.32635 1128.448683 1128.571016 1128.693349 1128.815682 1128.938015 1129.060348 1129.182682 1129.305015 1129.427348 1129.549681 1129.672014 1129.794347 1129.91668 1130.039013 1130.161346 1130.283679 1130.406012 1130.528345 1130.650678 1130.773012 1130.895345 1131.017678 1131.140011 1131.262344 1131.384677 1131.50701 1131.629343 1131.751676 1131.874009 1131.996342 1132.118675 1132.241008 1132.363342 1132.485675 1132.608008 1132.730341 1132.852674 1132.975007 1133.09734 1133.219673 1133.342006 1133.464339 1133.586672 1133.709005 1133.831338 1133.953672 1134.076005 1134.198338 1134.320671 1134.443004 1134.565337 1134.68767 1134.810003 1134.932336 1135.054669 1135.177002 1135.299335 1135.421668 1135.544002 1135.666335 1135.788668 1135.911001 1136.033334 1136.155667 1136.278 1136.400333 1136.522666 1136.644999 1136.767332 1136.889665 1137.011998 1137.134332 1137.256665 1137.378998 1137.501331 1137.623664 1137.745997 1137.86833 1137.990663 1138.112996 1138.235329 1138.357662 1138.479995 1138.602328 1138.724662 1138.846995 1138.969328 1139.091661 1139.213994 1139.336327 1139.45866 1139.580993 1139.703326 1139.825659 1139.947992 1140.070325
 
Qazi Zafar Iqbal
added a project goal
optimization,GA,BPSO,WDO,ACO,appliances scheduling,hybrid power generation,solar PV and diesel generator