Research Items (27)
- Jun 2018
Although future widespread use of plug-in electric vehicles (PEVs) will considerably reduce the greenhouse gas emissions, their charging demand will pose significant challenges to the grid. Aggregated charge scheduling of PEVs in parking lots (PLs) can mitigate the challenges, if the size and place of the PLs for PEVs are optimally determined. This paper proposes an optimization-based problem to not only determine the optimal size and place of PLs for PEVs, but also optimally schedule the charge and discharge of PEVs in the located PLs. The operation costs of distribution system, including the cost of purchasing energy from upstream grid and the cost of PEV charging in PLs, are considered as the objective of the proposed optimization problem, subject to the distribution system constraints. The proposed method is examined in a test system, considering different penetration levels for PEVs. In addition, the impact of results is investigated on the reliability of distribution system. The results show that decrements in the total cost of operation may lead to a lower reliability for the distribution system. The sensitivity of the results to the maximum charging rate of the parked PEVs in the located PLs is also reported in this paper.
- Apr 2018
Residential energy management (REM) systems facilitate the application of residential demand response (DR) programs to manage the increasing demand of electricity in power systems. The load curtailment at high price periods and the load shift from high-price to low-price periods are the main results of REM implementation, which may improve the technical and economical operation of the distribution systems. Customers' satisfaction should be considered in the REM procedure to motivate the customers to respond to the received price signals. This paper proposes an optimization-based REM to minimize not only the customer's energy cost but also customer dissatisfaction, which is modeled as a function of load curtailment. In addition, the impact of broad application of REM in bus 6 of RBTS is studied on the reliability of distribution system. To this end, two different methods for reliability evaluation is used to show the effect of load shift and load curtailment on the energy not supplied by the distribution system. The results verify the validity and effectiveness of the proposed REM approach and show the impact of application of REM programs with different penetration levels on the reliability of distribution system.
- Mar 2018
Expansion of cogeneration technologies, such as combined heat and power units, has boosted the growth of multicarrier energy systems. A two-step method is presented to enable residential demand response (DR) programmes in the multicarrier energy systems. In the first step, the energy management system at each home solves an optimisation problem to achieve the desired energy cost and demand schedule for the customer according to received price signals. In the second step, the system operator revises the demand scheduling by running another optimisation problem to minimise the total electrical losses, subject to the operational characteristics of electrical and natural gas systems. In order to persuade customers to participate in the DR programmes, it is guaranteed that the resulted cost of the second step is not more than the desired cost of the customer in the first step. Results of applying the proposed method, incorporating different penetration levels of customer participation in a time-of-use programme is studied in a test energy system. Simulation results verify the effectiveness of proposed method in minimising the total electrical losses, improving the operational characteristics of the energy system as well as providing customers' utilities.
- Nov 2017
This paper analyzes the energy consumption of buildings considering the uncertainty of structural and environmental parameters. To this end, two-point estimate method (2PEM) is used to model the uncertainties. EnergyPlus software is used in this paper to evaluate the energy consumption, the thermal comfort, and the energy cost of a building. We examine the proposed method in a retail building to show the effectiveness of the method in comparison with the Monte-Carlo Simulation and deterministic methods. The results show that the 2PEM method although may cause a bit accuracy loss, it can considerably reduce the simulation time by more than 97%. In addition, a sensitivity analysis is effectuated in this paper to investigate the impacts of different climate zones on the results of energy consumption analysis.
- May 2017
- 25th Iranian Conference on Electrical Engineering (ICEE 2017)
Home energy management (HEM) programs simplify the participation of residential customers in price-based demand response (DR) programs. If implemented widely, HEM programs could alter the load shape in distributions systems, and thus, impacting distribution systems reliability. Existing methods for evaluating distribution system reliability are not suited for evaluating the impact of change in daily load shape, caused by HEM, in distribution system reliability studies. In this paper, we propose a method to calculate energy-oriented indices, such as expected energy not supplied, by which the impact of HEM on distribution system reliability could be studied. Numerical results are provided to verify the proposed method.
- Dec 2016
Fast charging station is indispensable for widespread use of plug-in hybrid electric vehicle (PHEV), as it provides a mean to fully charge a PHEV in a short period of time. Application of electrical storage systems (ESSs) in fast charging stations is considered as a way to reduce operational costs of the station and to alleviate negative impacts of station operation on the power grid. This paper proposes an approach to determine the optimal size of the storage system for a fast charging station. In the first step, PHEV charging demand in a station is calculated considering PHEV characteristics as well as driving patterns of PHEV owners. The optimal size of ESS in the charging station is then determined, such that the station energy cost and the storage cost are minimized. The proposed approach considers various technical and economic issues, such as energy loss and life cycle cost of storage system. Using the proposed approach, a set of studies is conducted to verify the effectiveness and applicability of the proposed algorithm.
Residential Energy Management (REM) program is a demand response (DR) tool that automatically manages energy consumption of controllable household appliances to improve the energy consumption profile of a house according to electricity price. REM intends to only improve technical aspects of distribution systems, but also motivate customers for active participation in DR programs. In this regard, this paper proposes a two-level REM framework. In the first level, each customer runs an optimization problem to minimize his payment cost and sends the desired operation scheduling of appliances and the payment cost to the system operator. In the second level, a multiobjective (MO) optimization framework is designed to improve technical characteristics of the distribution system such as total load demand deviation, given the least desired payment cost of each customer. The objective functions of this MO optimization structure are to minimize deviation of distribution system load and to minimize costs of modifying the desired scheduling of customers. The proposed algorithm is mathematically modeled and applied to IEEE 34-node test feeder to prove its advantages for customers and system operators in comparison with the available REM strategies.
Going back and taking a quick glance at the history of developed countries prove that prosperity of any society is tightly intertwined with resiliency and sustainability of its preliminary infrastructures. Surely, in modern societies, electricity is among the most important infrastructures whose resiliency and sustainability is a key driving force toward development of the society. This is verified by the fact that, since the industrial revolution, per capita electricity consumption has taken as a key index showing the level of economic development and standard of living in a country. This paper focuses on the concept of resiliency and sustainability of electric power systems. The paper, initially, introduces the concept and evaluation procedure of power systems resiliency. Then, it strives to introduce the most challenging issues faced by resilient and sustainable power grids. The challenging issues are electricity load growth, energy crisis, environmental emissions and climate changes, unexpected events, aging infrastructures, and cyber challenges. Then, the most effective solutions proposed by power industry scientists and engineers are discussed. The solutions are asset management, renewable energy resources, demand response, controlled islanding and micro grids, and automation, self-healing , and monitoring systems. Finally, a typical sustainable and resilient power system is described.
- Feb 2016
This paper proposes a new framework for home energy management (HEM) in the context of renewable-based residential energy hub using a probabilistic optimization approach. Different energy converters and storages, including combined heat and power, a plug-in hybrid electric vehicle, a heat storage unit, solar panels, and generic household appliances, are considered in the energy hub. The customer's energy cost is considered as the objective of the HEM optimization problem and different operational limits of the energy hub components are modeled as the constraints. The two-point estimate method is incorporated in this paper to model the uncertainty associated with output power of the rooftop solar panels. Numerical results are provided to demonstrate the performance of the proposed approach.
- Jul 2015
This paper presents a residential energy hub model for a smart multi-carrier energy home consisting of plug-in hybrid electric vehicle (PHEV), combined heat and power (CHP), solar panels, and electrical storage system (ESS). The energy hub inputs are electricity and natural gas that provide electrical and heat demands at the output ports. In this paper, an optimization-based program is proposed to determine the optimal operation mode of the energy hub, to manage the energy consumption of responsive appliances, to schedule charging/discharging of PHEV and the storage system, and to coordinate solar panels operation with household responsive demand in response to day-ahead time-varying tariffs of electricity. The objective function is to minimize customer payment cost considering vehicle to grid (V2G) capability. Different case studies are conducted to probe the effectiveness of the proposed method and study the impacts of different electrical time-differentiated tariffs on the optimization results on daily and yearly basis.
- Jun 2015
- 2015 IEEE Eindhoven PowerTech
To tackle the air pollution issues, Plug-in Hybrid Electric Vehicles (PHEVs) are proposed as an appropriate solution. Charging a large amount of PHEV batteries, if not controlled, would have negative impacts on the distribution system. The control process of charging of these vehicles can be centralized in parking lots that may provide a chance for better coordination than the individual charging in houses. In this paper, an optimization-based approach is proposed to determine the optimum PHEV parking capacities in candidate nodes of the distribution system. In so doing, a profile for charging and discharging of PHEVs is developed in order to flatten the network load profile. Then, this profile is used in solving an optimization problem to minimize the distribution system losses. The outputs of the proposed method are the proper place for PHEV parking lots and optimum capacity for each parking. The application of the proposed method on the IEEE-34 node test feeder verifies the effectiveness of the method.
- Jun 2015
- 2015 IEEE 15th International Conference on Environment and Electrical Engineering (EEEIC)
This paper proposes a centralized optimization-based home energy management (HEM) scheme in a macro energy hub structure. An energy hub management system manages the aggregated load of a group of residential micro energy hubs to minimize the total load deviation. The operational characteristics of the household appliances and the threshold energy cost of the customers are incorporated in the propounded method to provide the customers' comfort. Numerical studies show the effectiveness of the proposed method performance.
- Feb 2015
One way of more efficiently utilizing the existing gas and electrical infrastructures is to consider them as one integrated system in planning and operation of energy systems. The energy hub framework is adopted to determine a modeling procedure for such multi carrier energy systems. This paper presents a residential energy hub model for a smart home. A residential combined heat and power (CHP) as a cogeneration technology, and a plug-in hybrid electric vehicle are employed in the model. Operation of the hub is optimized through a proposed optimization-based formulation. The objective is to minimize customer payment cost. Solving the problem determines how much of each energy carrier the hubs should consume and how they should be converted in order to meet the load at hub's outputs. Since home load management (HLM) plays a key role in realizing household demand response programs, performing HLM in the proposed residential energy hub model is also studied in this paper. To do this, the optimization problem is extended by considering different operational constraints of the responsive appliances determined by the customer. The proposed optimization-based formulation is applied to a home to deeply study the different aspects of the propounded method.
- Jan 2015
- Plug In Electric Vehicles in Smart Grids
Plug-in electric vehicles (PEVs) are identified as one of the motivating technologies in smart grid era. However, if their highly disruptive impacts on the distribution system are left unaddressed, it may obstruct both smart grid development and PEV adoption. This chapter develops a novel in-home PEV charging control (PCC) algorithm that schedules both the time and level of charging PEVs incorporating customer’s desired comfort level. This optimization-based problem attempts to achieve a trade-off between minimizing the electricity payment and minimizing the waiting time to fully charge the PEVs in presence of a time of use (TOU) pricing tariff combined with inclining block rates (IBRs). The projected algorithm is online in which each PEV is scheduled at its plug-in time, and the charge scheduling of plugged-in PEVs are updated when the next PEV is pluggedinto the home outlet. The proposed method is applied to a smart home with different number of PEVs and various levels of customer’s comfort. In addition, the impacts of solving PCC problems on the specifications of the IEEE 34-bus residential test feeder with different PEV penetration levels are investigated. The simulation results are presented to demonstrate the effectiveness and applicability of the proposed PEV charge scheduling scheme.
Application of residential demand response (DR) programs are currently realized up to a limited extent due to customers' difficulty in manually responding to the time-differentiated prices. As a solution, this paper proposes an automatic home load management (HLM) framework to achieve the household minimum payment as well as meet the operational constraints to provide customer's comfort. The projected HLM method controls on/off statuses of responsive appliances and the charging/discharging periods of plug-in hybrid electric vehicle (PHEV) and battery storage at home. This paper also studies the impacts of different time-varying tariffs, i.e., time of use (TOU), real time pricing (RTP), and inclining block rate (IBR), on the home load management (HLM). The study is effectuated in a smart home with electrical appliances, a PHEV, and a storage system. The simulation results are presented to demonstrate the effectiveness of the proposed HLM program. Peak of household load demand along with the customer payment costs are reported as the consequence of applying different pricings models in HLM.
- May 2014
- 2014 14th International Conference on Environment and Electrical Engineering (EEEIC)
- International Conference on Environment and Electrical Engineering
The presence of different energy carriers as well as the advent of new multi-generation technologies such as combined heat and power (CHP) at homes necessitates designing an integrated model for optimal operation of such multi-carrier energy home. A residential energy hub model including a CHP and a Plug-in hybrid electric vehicle (PHEV) is presented in this paper to show the multi-carrier energy system operation. In addition, this paper proposes an optimization-based formulation for PHEV charging control in the residential energy hub. The payment cost is minimized for the charge scheduling of PHEV through optimization of the residential energy hub operation in response to the time-differentiated pricing of electricity. The results show the effectiveness of the proposed PHEV charging control method in the residential energy hub from the customer and the utility viewpoints.
- Apr 2014
- Reliable and Sustainable Electric Power and Energy Systems Management: Reliability Modeling and Analysis of Smart Power Systems
Home automation is evolving with the objective of upgrading the living convenience. The load control is, however, conceived as its subsidiary function for economic benefits. In this chapter, the problem of home load controlling (HLC) is widely investigated through deterministic and probabilistic analysis. The behavior of plug-in hybrid electric vehicles (PHEVs) consumer, i.e., departure time, traveling time, and energy consumption, are assumed to be stochastic variables. Incorporation of these inherent uncertainties offers a solution with robust optimality in real world applications. More benefits are accordingly achievable compared with deterministic solutions. The optimization problem is formulated based on the mixed-integer programming (MIP) fashion since present commercial high-performance solvers guarantee the optimality of solutions. Numerical studies are conducted in order to illustrate the effectiveness of the model which clarifies the practicality of the proposed approach. A variety of sensitivity analyses are performed to demonstrate the effectiveness of the method in different conditions.
As the number of plug-in electric vehicles (PEVs) increases, so might their issues and impacts on the power system performance. Toward eliminating the negative impacts of PEVs on the power system, installation of a charging controller at customers' homes, which addresses such issues and brings convenience for customers, is fundamentally required in the smart grid era. This paper develops a novel in-home PEV charge/discharge scheduling method that employs vehicle-to-home (V2H) capability to schedule level of charging/discharging at each time slot. In doing so, a household controller minimizes customer payment cost and reliability cost. The proposed charging algorithm not only responds to time-varying tariffs but can also manage the home outage by supplying household appliances during the home load interruption. The proposed method is verified and tested with different case studies. Results show that applying the proposed method leads to significant decrement in home peak load and customer costs, i.e., payment and interruption costs.
This paper proposes a novel optimization based home load control (HLC) to manage the operation periods of responsive electrical appliances, determine several recommended operation periods for nonresponsive appliances, and schedule the charge/discharge cycling of plug-in hybrid electric vehicle (PHEV) considering various customer preferences. The customer preferences are in the format of payment cost, interruption cost, and different operational constraints. The projected algorithm is online, in which household appliances are initially scheduled based on the payment cost, and when the home load is interrupted, the scheduling will be updated to minimize customer interruption cost. Due to vehicle to home capability of PHEV, the home outage can be managed through solving the proposed optimization problem. Several realistic case studies are carried out to examine the performance of the suggested method. In addition, the impacts of common electricity tariffs on the HLC results are investigated. The results reveal that employing the proposed HLC program benefits not only the customers by reducing their payment and interruption costs, but also utility companies by decreasing the peak load of the aggregate load demand.
Despite the economic and environmental advantages of plug-in hybrid electric vehicles (PHEVs), the increased utilization of PHEVs brings up new concerns for power distribution system decision makers. Impacts of PHEVs on distribution networks, although have been proven to be noticeable, have not been thoroughly investigated for future years. In this paper, a comprehensive model is proposed to study the PHEV impacts on residential distribution systems. In so doing, PHEV fundamental characteristics, i.e., PHEV battery capacity, PHEV state of charge (SOC), and PHEV energy consumption in daily trips, are accurately modeled. As some of these effective characteristics depend on vehicle owner's behavior, their behavior and interests are considered in the proposed model. Also, to get a more practical model of PHEVs, the number of vehicles in a residential distribution network, the PHEV penetration level for upcoming years, distribution of PHEVs in the network, and estimation of household load growth for upcoming years are extracted from related published reports. The proposed model is applied to the IEEE 34-node test feeder, and PHEV impacts on residential distribution network are studied in different time horizons. A sensitivity analysis is also performed to demonstrate the effects of PHEV operation modes on the network load profile.
- Apr 2013
- Electrical Power Distribution Networks (EPDC), 2013 18th Conference on
- Conference on Electrical Power Distribution Networks
Demand response (DR) as a state-of-the-art program is accommodated in the energy efficiency contexts of the smart grid. Lack of the customer knowledge about how to respond to the time-differentiated tariffs and offered controlling signals is the major obstacle in the way of broad DR implementing. As a solution, an optimization method, namely load control (LC), is proposed to automatically control the on/off status of the responsive appliances in a smart home. This paper focuses on the direct load control (DLC) program in the category of incentive-based DR programs. LC is extended to consider inconvenience cost of the DLC implementation for DLC program participants. Outputs of the extended LC would be an advice for the customer to determine whether it is financially profitable to participate in the offered DLC program or not. Numerical studies are effectuated to investigate different features of the LC and DLC program.
- May 2012
A massive focus has recently been made on demand response (DR) programs, aimed to the electricity price reduction, reliability improvement, and energy efficiency. Basically, DR programs are divided into twofold main categories, namely incentive-based programs and price- or time-based programs. The focus of this paper is on priced-based DR programs including consumer responses to the time differentiated pricing. Home load management (HLM) program is designed to control responsive appliances and charging/discharging cycles of plug-in hybrid electric vehicles (PHEVs) by the consumer. Uncertain parameters associated with PHEV, i.e. its departure/travelling time and energy consumption as well as the grid unavailability in serving the loads are incorporated in the proposed probabilistic HLM model. Numerical simulations are conducted to illustrate the investigated notions and to verify the advantages of the developed model.
- Jan 2012
- Advances in Power System Control, Operation and Management (APSCOM 2012), 9th IET International Conference on
- International Conference on Advances in Power System Control, Operation and Management
Plug-in hybrid electric vehicle (PHEV) technology provides one of the most promising solutions to tackle the threatening challenges such as air pollution in urban areas. Dramatic increases in the number of PHEVs could have major impacts on power system operations because of their high electricity demand. From the distribution system operator facet, distribution system congestion during PHEVs' charging is an economic and security concern. It is, therefore, necessary to investigate the effects of widespread using of PHEVs on the performance of distribution networks. In this paper, PHEV characteristics are exactly studied and a comprehensive model for investigation of PHEV impacts is achieved. The results would likely demonstrate distribution congestion arising from using PHEVs. Controlled charging of PHEVs is a possible solution to the distribution congestion problem. In this work, optimal charging algorithm is developed which minimizes the electrical charging payment of customers. The optimization problem is solved by energy schedulers in each home. The output of the problem is the charging level for PHEVs in each period of the scheduling time. Results illustrate that due to noticeable likeness between the load behavior and tariffs, minimizing customer cost would likely lead to shave peak load and prevent distribution congestion.
One of the most important issues in the smart grid is to quantitatively assess the impacts of distributed energy resources (DER) on the distribution system reliability. Solar cells (SCs) as developing DERs are normally placed close to the load centers. In this paper, a new algorithm is developed to evaluate distribution system reliability, considering SCs in the vicinity of the end-users. The probabilistic nature of the demand and SC power output are investigated to solve challenges of integrating these intermittent resources with the distribution system. In a smart home, to handle the variation of SC generation, solar load controller (SLC) is utilized to match load and generation of SCs during the islanding mode. Harmonizing load and generation by SLC may cause continual fluctuation in the on/off mode of appliances. In this paper, a structure is proposed to supply the critical load throughout periods in which SC cannot supply the entire associated demand. Simulation results reveal that the proposed method outperforms the conventional one, particularly from the accuracy points of view, while keeping the simplicity and elegance in a reasonable range. Numerical simulations are investigated to verify the miscellaneous aspects of the proposed approach.