Science topic

Smart Grid - Science topic

It is an open discussion about Smart Grid issues for professionals, students and everyone who is interested in modernizing the power grid. Let’s share our thoughts, views and concerns for realizing the Smart Grid!
Questions related to Smart Grid
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Is petri net a state machine? Is it used in controls? I am interested in learning about the applications of petri-net especially in power/smart grids.
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A Petri Net is a graph model for the control behavior of systems exhibiting concurrency in their operation. The graph is bipartite, the two node types being places drawn as circles, and transitions drawn as bars. The arcs of the graph are directed and run from places to transitions or vice versa.
Chapter Petri Nets
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I want to detect the change in time-series data using RNN-LSTM. I know how to do it with supervised learning, but unable to do the same with unsupervised learning. In this case, I have time-series data for the electricity consumption of a customer with distorted patterns after some date. So before that date, the consumption patterns seem normal (no major change). After that date, the consumption sharply decreased as compared to the previous patterns. Here, I want to detect the change on the day when the pattern seems not normal. I am searching for a way forward for my problem.
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U can do conversion of unsupervised to supervised at initial phase of prediction process.
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I need a project topic on smart grid technology. please help.
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Smart Grid includes many aspects like communication, control, etc. So it actually depends on your major. However, the most important for you to know is to search for the recent issues or problems related to your major in smart grid and choose one to try to solve considering the main aims of developing smart grid is to optimize the utilization of consumption and production of energy
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I am working on energy forecasting and anomaly detection. I need to find looking energy consumption dataset.
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Our work is similar to what you are looking for. We performed load modelling for getting energy consumption data
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Hi,
can any one provide me latest journals on smartgrid
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I would think this list includes:
IET Smart Grids
IEEE Transactions on Smart Grid
International Journal of Smart Grid
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Can anyone please elucidate the difference between Euclidean and Non-Euclidean Space? I have seen some literatures where they haver mentioned social networks, sensor networks etc as examples of non-euclidean spaces. Is a power grid also an example of non-Euclidean?
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I am confused. Your citations appear to be mostly concerned with animal or machine learning in non-Euclidean spaces. Which of these citations directly discusses electrical power systems, such as the national electrica power grid? And what problems, concerning electrical power grids, can only be solved by the non-Euclidean space approach that cannot be solved by the old 2-dimensional Euclidean representation of such a network?
Regards,
Thomas Cuff
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Good Day Researchers,
Kindly refer to some study material to understand the mathematics of reinforced learning and its implementation on MATLAB.
Regards
Mukul
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I'm not an expert on any MATLAB implementations, since I mainly use Python for DRL projects.
However, I can give you some study materials.
I suggest you to take a look at "Reinforcement Learning, second edition: An Introduction" (Sutton & Barto). This book is very well written and they put a lot of effort to help you understand. You can find its open source version online (just search it on google).
If you don't want (or like) to read, then "RL Course by David Silver" on Youtube is another way to go.
From there, you can begin to look for more advanced algorithms (Deep Reinforcement Learning).
I hope I've been helpful!
Raoul
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Power Network Expansion Planning is the problem of deciding the new transmission lines that should be added to an existing transmission network in order to satisfy system objectives efficiently. It is one of the main strategic decisions in power systems and has a deep, long-lasting impact on the operation of the system. Several challenges such as deregulation, renewable penetration, large-scale generation projects, market integration, and regional planning are discussed in the literature to some extent.
In the context of the smart grid, what can be the potential future challenges in terms of different scenarios, applications, modeling, solution, and novel devices in the network?
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Two main problems in the perspective of SG:
*Integration of Microgrid, while considering uncertain factors and limitations of the present grid.
*Integration of charging stations for EVs taking into view users' profiles and traditional grid capacity.
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1. Considering Two Area Four Machines system, I would like to get some PMU data from Area 1 to Area 2. I am interested in finding out the maximum communication delay that can occur so that inter-area oscillations can be damped out by a controller.
2. If controller receives the data after very long time due to channel imperfections, then what is the possible action to be taken to damp out inter-area oscillations?
3. Does anyone has the knowledge on the practical value of communication delay in real-time power system(smart grid)?
Thanks in advance!!
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Somepne please help me where to learn the simulation of Smart Grid on YouTube or other bookr esources?
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Does adding renewable energy sources to smart grid change the price?
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We analyse energy market management performance of a fractional-order PI controller in the case of communication and operation delays in a multi-source energy market model. Market simulation results are discussed to demonstrate the possible advantages of the fractional-order PI controller for smart grid energy market managements.
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I want work on my project in the field of "Microgrid." I need a test system of microgrid in digsilent or matlab simulink. If anyone here has this file, please give me.
Thanks guys!
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You can also use Simscape Power Systems to Simulate Microgrids
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As an electrical researcher, which journal would you choose as your preferred journal for publishing your research, if possible?
This selection includes a maximum of three journals (in order of preference) and the selection criteria can be based on any of the trends (power system, power electronic, smart grid, etc.).
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IEEE!
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Hello,
I'm currently enrolled in my last M.S. Renewable Energies & Intelligent Networks trimester before I need to work on my master thesis. My prior degree is a B.E. in Applied Computer & Communication Technology (focus: Software Engineering) and an A.S. in Computer Engineering Technology. I'm looking for some master thesis topic suggestions in the area of Smart Grids which would ideally prepare me for (an engineering) remote job in the field. We had to take a class called automation which covered some topics about smart grids and we had to program using PLC and I enjoyed it. As I'm unfamiliar with all of the smart grid topics that would lead to my goal, I would like your opinions about suitable topics for my master thesis. Btw: Assuming that most remote jobs are probably programming related, I have to note that while I've had a lot of java programming classes, I'm not very interested in it but would prefer PLC, C, Embedded Systems or similar.
There is also a project we need to work on which can be part of our master thesis. For this topic, I would like to connect a few electrical devices (loads and generators) in an electrical circuit and create a program algorithm which decides when to store energy in a battery, when to switch off electrical devices or when to feed back excessive energy to the grid. I'd also welcome some ideas for that.
Finally, I'm wondering which types of remote jobs exist for engineers that are not software engineering?
Thank you.
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Hardware in the loop and Droop Controls for SER integration.
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Hello Researchers, I would like to do both simulation and implementation level research work on the smart grid. How should I start from the beginner's level?
I have completed Bsc in EEE.
Any suggestion would be helpful.
Thanks in advance.
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First of all, you should decide the location of your Smart-Grid system.
Then, you can select what types of renewables (Solar PV+ what ?) will be installed in your system. Probably, you will add the Electric Vehicles charging systems at the Smart Homes of your Smart Grid System.
You need to consider the interconnection technology of your Smart Grid System.
You have to collect the data and then, model and simulate your Smart Grid System in the supportive software tool.
After that, you need to analyze your simulation results.
According to the amount of research funding, you can implement your Smart Grid System.
Then, you can consider your Smart Grid System be connected with the National Grid System and investigate what impacts from your System.
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Demand Side Management is one of the key tools in smart grids. It is aimed to control and manipulate of the demand by DSM. Demand response programs in DSM provide an option to control and manage the demands via incentives or electricity price. Which performance indices are used in DSM and demand response programs in order to manage the demand? Also, which performance indices are used in DSM in order to evaluate the effectiveness of the DSM?
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Thank you for your answer Dr. Qamar Ul Islam . But I want to learn and discuss the metrics or indices that can be used in evaluation of the DSM performance.
Best regards,
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Smart grid stability isssues and prediction of instability using Machine learning techniques
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The stability issues are basically based on the type of disturbances and the controllers used in the system
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IS there any literature that analyze selection of window length of window in rooling/moving RMS of voltage signal?
I log data from oscilloscope, and then I calculate RMS voltage, but I am not sure the length of the window? Are there any rules about this?
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Which algorithm is best for energy management in smart grid?
To work on 3 objectives, like
1. operating cost
2. pollution emissions
3. availability of renewable energy energy sources.
Which algorithm (must new) can we use?
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I suggest MCDM techniques in combination with commercial software such as HOMER, PVSYST, TSOL, and etc.
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Kindly suggest some upcoming research areas/ challenges to explore in (but not limited to) sustainable planning, and performance assessment of hybrid renewable grids.
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These investigations can provide you with a very comprehensive overview.
  • A hybrid renewable energy system for a North American off-grid community
  • Optimization of PV-biomass-diesel and grid base hybrid energy systems for rural electrification by using HOMER
  • Optimal design and techno-economic analysis of a solar-wind-biomass off-grid hybrid power system for remote rural electrification: A case study of west China
  • A thorough investigation on hybrid application of biomass gasifier and PV resources to meet energy needs for a northern rural off-grid region of Bangladesh: A potential solution to replicate in rural off-grid areas or not?
  • Heuristic indicators for the design of community off-grid electrification systems based on multiple renewable energies
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The Smart-Grid Revolution Starts in Boulder, Colorado, who were the stakeholders of this project and what conflict could arise with the stakeholders?
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The Smart-Grid Revolution Starts in Boulder, Colorado Question 1: Are the triple ... A conflict that could occur would be whether the smart grid will take away ... major portion of this project had to do with carefully managing all the stakeholders.
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I am interested to see the impact of Renewable Energy Sources on the frequency regulation on a smart grid. Any recommended references and papers?
Thanks!
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Proposed this papers:
DOI: 10.1109/TIA.2020.3024350
DOI: 10.1007/s12652-020-02260-z
DOI: 10.1016/j.ijepes.2021.106814
DOI: 10.1016/j.jestch.2019.03.007
DOI: 10.1109/TIE.2020.2984419
DOI: 10.1016/j.isatra.2020.12.026
DOI: 10.1016/j.epsr.2021.107339
Best regards.
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I have proposed an algorithm for energy efficiency at home. I want to implement my model and algorithm to verify the claims and generate results. My parameters are predefined (Switching-on/off timings, Load categories, integration of renewable energies, ToU, When to shift loads at other energy sources .etc). Please recommend me software to do the simulation (Electrical Load/network analysis). I have no time do make functions on MatLab. Tell me some easy to use and GUI based tools.
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TRNSYS es un programa de simulación utilizado principalmente en los campos de la ingeniería de las energías renovables y la simulación de sistemas solares pasivos, así como el diseño solar activo. TRNSYS es un paquete de software comercial desarrollado en la Universidad de Wisconsin.
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Hello folks!I just need your help regarding where to learn the Simulation of Smart Grid?
Kindly guide me please for my M.Sc Thesis.
TIA
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Hello Engineers;
Can anyone please help me regarding simulation for single-phase smart grid tie inverter?
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I agree with Mr. Hadi
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Dear Experts,
Greetings
I am Dr. Vipul N Rajput working as Associate Professor in Dr. Jivraj Mehta Institute of technology. I am developing quantitative approaches to rank components and technologies for smart grid in India. As a part of my project objective, I would like to incorporate your opinions as an expert.
It is extremely useful to understand the expert stakeholder’s perspective for transforming into complex systems such smart grids due to interactive and non-hierarchical structure. The motivation of this exercise is to improve focus on silos of smart grid development by incorporating experts’ opinions. The responses will be used for ranking these silos so as to recommend synergistic development. This tool can be further used as a scientific rationale for Smart Grid policy development as well. For this exercise, I am attaching an objective questionnaire. Also, the brief introduction about the criteria mentioned in questionnaire can be found in attached document (Definitions_SmartGrid_Criteria).
Your expertise and knowledge in the development of smart grid will definitely help our project positively. You are requested to fill out the questionnaire with your kind perusal. Please attach the response document and convey suggestions, if any.
These responses will be solely used for the research and academic purpose. Your response will remain anonymous.
Once we have sufficient responses, we will share the anonymous responses collected through this discussion for the research community. If you are interested in collaborating for this work, please leave a message in this discussion or send an Email to vipulrajput16986@gmail.com.
Thank You.
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You are welcome.
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Dear all,
I would like to test Power Quality algorithms and indexes for DC grids, DC distribution networks, including DC electrified transportation systems, and show performance in real conditions (showing for example typical ripple, presence of supraharmonics, and most of all typical transients due to load step, variability of PhotoVoltaic and wind energy sources, etc.)
As for DC electrified transportation systems I have several recordings of pantograph voltage and current in 3 kV and 1.5 kV lines (railways and metros).
Specific question: are there accessible datasets or repositories of such voltage and current sampled waveforms for DC grids, microgrids, distribution networks? or do you yourselves have such recordings and could make them available?
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Grustno. Received no answers so far ... :(
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Dear Sir/Madam,
I would like to see if anyone is interested in collaborating on some research papers. I work in the fields of SMART GRID, SMART BUILDINGS, OPTIMIZATION, and ENERGY MANAGEMENT.
If you are interested, could you send me a private text, please?
Thanks,
have a nice day!
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Many thanks for giving us the open invitation. I am interested to collaborate with you in the said area.
Looking forward to hearing from you soon
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The data collected from various measurement devices often contains erroneous values - such as noise, missing values, etc. What are the popular techniques for pre-processing measurement data in Smart Grid/Power System?
Citing references will be really helpful. Thanks in advance!
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Any ideas for dummies in the Energy sector?
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Kalim Ullah , Ravindrakumar Yadav , Abdelghani Rouini thanks a lot. All materials were very helpful
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I’m a graduate student and I’m going To start my thesis research , could you help me to find something related to the islanding detection to research about ,thank you at all
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i am interested too and follow
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PMU data can go missing due to several factors - faulty PMU or PDC or communication channel, cyber attack, etc.
Bad data can be also caused due to some of the above reasons or maybe due to some valid reasons such as faults occurring in the power system.
But be the reason valid or invalid, the signal processing algorithm will consider the data to be missing irrespective of the cause and could treat it as a fault and can opt for control strategies accordingly.
My question is directed at gaining insights about how to identify whether the missing/bad data occurred due to a valid (fault, etc) or invalid reason (cyberattack, device failure, etc) by monitoring any other data from any other device or using any algorithm.
If you can share any references, it will also be quite useful.
Thanks a lot in advance.
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It may be by suitably extrapolating from exact neighboring element data (bus or line depending upon the system) at that very point of time. It is some sort of estimation to be applied.
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I want to combine Project management and renewable energy. Or Smart grid and RE, or project management
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"Simulation and modeling of fluid flowing through absorber tube of solar parabolic trough".
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Is power-to-gas a possible solution to this issue? Storing renewable energy in the form of H2 and CH4 and using them as fuels can increase the penetration of renewable energy in the transportation sector?
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I agree with Mohammed. In addition, sustainable H2 and CH4 (from renewables) can be stored in the Natural Gas Pipeline network and underground for seasonal balancing of Electricity Demand and Supply. Sustainable H2 and methane can also power heavy duty fuel cell vehicles year-round. When wildfires and other natural disasters crash the grid, or lead to rolling preventive blackouts, the redundancy and security of the underground natural gas pipeline network and storage fields can provide stable energy supplies to distributed fuel cells.
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1. How often do they send GOOSE packets?
2. Who goes to fast transmission mode at a event of failure?
3. Where in the distribution grid will they be deployed in the future? at the beginning of each feeder for example?
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If you continue in this area, you will discover that the answer to all non-trivial questions begins "It depends, ..."
IEC 61850 itself defines a number of performance classes for different purposes. For protection functions inside transmission substations, a maximum data transfer time of 3 to 10ms (a quarter to a half cycle of 50 or 60Hz) is required. In distribution systems, the times are longer (e.g. five times longer) because of the differences in the design and requirements for protection in transmission and distribution. For SCADA functions reporting to an operator, 1 second is acceptable. File transfer (e.g. fault records) is even slower.
GOOSE is just one possible mechanism. It is appropriate for some functions (and was designed to meet high-speed process coordination needs of protection systems), but not for others. There is no single technology that is always a good way of meeting every requirement, and that applies to GOOSE as well as everything else.
You might think you are asking a simple question, but the answer depends on the context. To get a clearer answer, you also need to explain the background of the application you are asking about.
Your third question seems to ask "where are IEDs used". This is related to functions and has little or nothing to do with the communication protocol. Over time, the answer to this question will change as intelligent devices are used closer and closer to the "edge" of the grid. Once upon a time there were no IEDs: All protection and control devices in the grid were electromechanical. Over time, the centralized parts (e.. transmission substation protection schemes) have been updated to IEDs. Now IEDs are used across the distribution grid (e.g. pole-top reclosers, fault passage indicators, etc.). In the future they will be in the consumer's home, office or factory. You can consider todays' smart meters and building automation systems as early kinds of consumer-level IEDs. Over time there will be an increasing number of intelligent devices in the grid, with different functions and different communication requirements.
All of this is part of the complex system of systems that is the power grid. There is almost unlimited potential to delve into the details of each part and consider the different ways that the parts can interact. You can build a career spanning decades to become expert in just a small area...
I wish you well in your studies.
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Please can anybody help me by providing some good low impact non paid journal for article related to "smart grid cyber security".
Thanks
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I want start to work with Smart Grid Applications,
How can start small example from demos?
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Smart grid systems are characterized by high complexity due to interactions between a traditional passive network and active power electronic components, coupled using communication links. Additionally, automation and information technology plays an important role in order to operate and optimize such cyber-physical energy systems with a high(er) penetration of fluctuating renewable generation and controllable loads.
The Smart grid simulations in MATLAB / Simulink:
Best regards
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Considering the recent trends in electrical engineering and new emerging topics in electrical engineering and considering the multidisciplinary areas of research (esp. smart grid), all electrical engineers must have a good command of programming. In this respect, taking into consideration both the academic and industrial requirements, which programming language would be the best choice and why?
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For a new programming language, specifically for Electrical Engineering applications, I you suggest : The Python.
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How does a nano grid works and it's typical costs
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Distributed generation, mainally wind turbains, photovltaic systems, energy storage system, and electrical vehical. the nanogrid is offered an energy for a buliding, then these grids are connected togather to form a micro-grid.
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Efficiency and emission reductions are two identified related factors of energy - environment topics.
How are you utilizing artificial intelligence (AI) towards more energy efficient systems while decreasing emissions?
Further, what technical challenges / barriers are you dealing with while applying AI to specific energy - environment problems?
This topic is very broad and involves convergent teams of scientists and engineers. Specific examples include: smart traffic systems that can route traffic decreasing idling or traveling time(s), design that reduces weights of vehicles, reduction of emissions from chemical and petrochemical processing equipment, and the use of mixed energy generation sources to meet demand while reducing impact.
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One of the upcoming area AI in Green Computing discusses the same. I have tried to use AI in predicting AQI values of air pollutants. I have also considered sleep modes of sensors and their switching when they are idle. Maybe these articles may help you.....1. http://www.cit.iit.bas.bg/CIT-2020/v-20-2/10341-Volume20_Issue_2-10_paper.pdf 2.
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What can be the area of focus? I request eminent researchers in the field to recommend the algorithms on data analysis for Smart Grid for better understanding. I request to consider open source platforms. Thanks in advance.
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Hi,
Three elements go together here: a well-defined objective, the proper algorithm, and sufficient data of good quality. Below are some suggestions and a link to a publicly available dataset:
> An interesting research objective in smart grids nowadays can perhaps be cyber risk and cyber-attacks detection, or fault detection/ identification, and diagnosis; These are classification problems. Other trends are performance degradation or failure prediction, intelligent events management, and power/demand forecasting; These are approached through regression algorithms.
> From a defined objective, you can find abundant machine learning and statistical classification and regression algorithms that suit the objective and perform better with the characteristics of the system and the data.
>It is so important to consider data before starting a new project. A set of experimental data files is uploaded recently and they are now publicly available for research projects covering photovoltaic microgrids; fault detection & diagnosis; data analysis; and machine learning.
>>This is a link to data which I hope are found useful:
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Dear All,
For my research about data mining in building energy, I need residential energy consumption' but with these requirements:
-appliance level (like refrigerator..)
-at least 40 valid homes
-at least 12-hour resolution(=recording intervals)
-at least 6 months duration
I thoroughly searched for it for about two months! My ultimate choice, "Pecan Street" unfortunately newly restricted its free access mode!
I would be grateful if anyone recommends me similar data.
Your assistance is appreciated in advance.
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I am grateful for your answers. I've checked them all.
Unfortunately, all were far from what I mentioned as requirements. I'd checked Kaggle, UCI, CER, ISSDA, etc., in the first week!
I value your consideration so much; Thank you.
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I am working on network/ switch reconfiguration for balanced/unbalanced distribution system. Please suggest best papers with proper results and understanding.
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Dear ;
please check the attached files :
Article Reconfiguration of power distribution systems using probabilistic reliability models Full-text available July 2011 B. Amanulla Saikat Chakrabarti S. N. Singh
Regards
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Working on virtual management of PV system networks, I came accross with "ramp-rate control" that seems pretty plausible-simple scenario. The question crossed my mind is what is the role of PV system performance forecast in a power grid where PV generation is just a suplimentary, i.e. PV generation is a small part of the total capacity. In this case you don't very much rely on PV generation and you can cut it off if it cause fluctuation, why forecast it?
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yes, it is very important
Mankind has used and still consumes a large proportion of the planet's non-renewable energy resources such as oil, natural gas and coal to meet its energy needs. In just the past two decades, other renewable energy sources such as solar photovoltaics and wind energy have become somewhat related to generating electricity in the world.
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when we connect power converter with pv system the value of voltage will fluctuate across the power converter output, then how to retain a desired constant value at power converter output for its further integration with grid, kindly suggest some models or papers for refernce?? 
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The photovoltaic (PV) module exhibits a nonlinear characteristic. Consequently, the power output from the PV array is frequently subjected to fluctuate with a transition in solar insolation level and temperature. Based on this understanding, a maximum power point (MPP) tracker is practically equipped with the DC-DC converter to ensure the maximum power evacuation from the PV array when exposed to equal and unequal solar insolation or partial sharing scenario. In practice, the DC-DC converter is also responsible for the instantaneous power balance between the PV unit and DC-side collector bus. Notably, the PV power or voltage fluctuations as a result of solar insolation and temperature change can be effectively restricted to the normal working limit by employing a suitable variable perturbation-size MPP tracker. Note that, a suitably fixed duty cycle (D) is required to be provided to escalate the input voltage generated by the PV array. Furthermore, the fixed-duty cycle (D) must be added with the duty cycle generated by the MPP tracker. It is important to note that, selection of inappropriate duty cycle may cause the voltage fluctuations in the converter output. Additionally, if the envisaged PV unit is a type of grid-integrated then you may employ amalgamation of classical proportional-integral (PI) based feedback controller together with PV feed-forward term in the voltage control loop (VCL) of the control structure to limit the PV voltage fluctuations.
Hope the explanation provided above helps..!
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In this digitization age, we all know that Artificial Intelligence or AI is an extremely popular topic of research and development. For electrical power system and renewable energy sources, what is the expected future prospect and revolution by AI? How the electrical industry will benefit from the Industry Revolution (IR) 4.0 digital transformation with AI? Is it possible to integrate all existing conventional electrical power system with AI to accelerate the integration of digital and electrical & electronics?
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Electric Utilities like every other business, exist to provide a service and make a profit. Some problems associated with the electricity industry, include: low productivity and data analysis, customer support and personalization, and fraud. AI can be implemented to carry out tedious, repetitive processes, currently carried out by humans. This improves productivity and complex analytical tasks by automating business processes resulting in efficiency and reduce overheads. Looking at the power plant in particular, in areas like preventative maintenance, AI can be used to predict and prevent issues before they turn into major problems that impact productivity adversely, leading to blackouts, brownouts or breakdowns. AI can detect and fend off security risk and reduce network downtime and mitigates against loss of supply and finances. AI can be used by utilities in cyber-security in a preventative and predictive manner; identify trends based on historical data (and in real-time), provide intelligent prediction to empower future customer behaviour. The results will be improved accuracy, personalization of service and higher efficiency. AI will continue to make inroads in transforming the electric power industry, and already has a foothold in areas like load forecasting and plant condition monitoring. We must be careful about the misconceptions of AI, which are often due to science fiction (SciFi) and extreme entertainment, which have no place in modern reality. All AI right now is narrow AI and the fundamental technologies are: computer vision (CV), natural language processing (NLP) and reinforced learning (RL). AI is transformative and can deliver critical business outcomes for electric utilities.
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In domestic field, washing machine and dishwasher loads are categorized as controllable- shiftable loads.
Nowadays, what are most known published works on this topic?
In particular, what is the most effective approach in formulating such kind of loads?
What are the most effective algorithms which are able to schedule in real time the cycle of such loads without assuming to know a priori the future energy demand?
What are is the most common objective function used by a training (optimization) algorithm?
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In reality, the metering infrastructure at LV level is limited and they're expensive. Therefore, any practical optimization algorithm has to work with the limited data. This could be one of the reasons why we still prefer rule based control. But prediction based optimal control such as MPC is gaining momentum at least in research fields. I don't know how long it will take for those technologies to get adapted in large scale.
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We know, In MATLAB software working in two types of environment. MATLAB Coding Script and MATLAB Simulink. For optimization smart grid operation many respected authors used different types of metaheuristic algorithms to solve this problem. The maximum author chose MATLAB Code to solve metaheuristic algorithms. Now my question: is it efficient to use MATLAB Simulink to replace MATLAB code to solve metaheuristic algorithms for optimization smart grid operation?
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The answer is both!
Either you can use codes to implement your study or do the same procedure in a simulator like Simulink. However, it depends on 'your' problem. If you are developing an algorithm, iterative procedure, optimization problem, or a study about a large network and agents with myriads of variables, parameters, and tunings, my advice is 'Matlab Code'. Otherwise, if you are studying on a small network in which you want to observe the operation and the responses of different components, and also you already can find all of them in the Simulink environment, you'd better use Simulink.
Good Luck!
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Is there differents between 5G and orhers ICT infrastrure in terms of smart grid applications? For example, is there any different between 5G and LTE?
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Mahdi, please note that 5G is widely believed to be smarter, faster, and more efficient than 4G. It promises mobile data speeds that far outstrip the fastest home broadband network currently available to consumers. With speeds of up to 100 gigabits per second, 5G is set to be as much as 100 times faster than 4G. Therefore, it is able to handle more data exchange capability and may help the controllers of renewable resources, etc to respond faster and thus, improve the dynamic performance of smart grids. However, what's more important, I think, is the topology and configuration of the communication system. It is expected that future communications systems configurations are inclined to be more distributed through distributed micro-antenna.
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I want to calculate the transmission time of electricity (for example 20kw) in smart grid between two nodes (consumer and producer) , is there any formula i can use !!!
can anyone help me, thanks in advance
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While endorsing views of Mahdi Saadatmand and Madhab Roy, no matter through the smart or non-smart electric network when electricity flows with the speed of light when the conductor is bare conductor. However, in the case of cable it is bit slower, mathematically arrived or estimated at by dividing that speed by the square root of relative dielectric constant of cable insulation with respect to air.
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i know the difference between smart grid and micro grid , but in term of infrastructure, i dont know what is the difference between them. Anyone can help me, please?
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Smart Grids simply refers to the integration of ICT infrastructure to the existing power scheme for improvements in power delivery control, monitoring and delivery scheme. For short, it's simply making the power grid intelligent to achieve multidimensional information flow to enhance power delivery scheme....while Micro grid refers to a localized version of power grid usually separate from the national grid for power supplies to remote or isolated areas. Microgrid may or may not be smart. This means the concept of smart grid applies to any unit of power system delivery scheme that's made intelligent, irrespective of the size.
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Try to mention the scale , in descending order of importance , by indicating the indices of power quality of the smart grid.
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Indices and standards of power-quality for smart-grid, are basically the same as conventional systems
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Is there any code / package / script to automatically generate single-line diagrams from PYPOWER/MATPOWER casefile or IEEE CDF formats?
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Matlab now has a toolbox for graph theory and complex networks.
i used that toolbox to convert MATPOWER data to a graph, and then generate a plot.
it was useful for me when i wanted to visualize different distribution networks i was working on.
keep in mind that distribution networks don't have loops. so the graphs were pretty neat. but for a large meshed system, the graph would look ugly. matlab wouldn't go out of its way to make a neat graph (with no lines crossing).
the code i wrote throws different kinds of errors everytime i run it, and everytime i debug it or do something to fix that particular problem.
if you're a matlab expert/novahoo, i can share that code with you. you're going to need to look under the cover and debug an error when you get one
otherwise, wouldn't recommend it
you can write your own code. the key matlab commands are:
buidl a graph with:
my_graph = digraph(......)
or
my_graph = graph(.....)
and then
plot(my_graph);
in my code, i tried to color code the different nodes, and represent the impedance or flow size on a transmission line by the line's thickness
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Are there any standards regarding islanded micro grids applicable in terms of general operation, especially regarding AC/DC converters with battery, PV or other sources. 
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Dear Colleagues,
Energy communities are facing changing regulatory and technological landscapes, which represent both opportunities for and barriers to their development. On the one hand, the new European clean energy regulation envisages important roles for energy communities in energy systems and provides enabling conditions for their deployment (EU, 2019). Furthermore, new types of interactions among active consumers, prosumers and prosumagers are emerging, often facilitated by decentralized storage, smart grid technologies, distributed energy resources and other small-scale technologies, as well as local exchanges enabled by innovative blockchain-based peer-to-peer trading platforms and local energy markets (Giotitsas et al., 2015; Hahnel et al., 2019; Koirala et al., 2018b, 2019; Parra et al., 2016, 2017). All these evolutions create new opportunities for energy communities to play an active role in transitioning towards more sustainable energy systems (Devine-Wright, 2019; van der Schoor and Scholtens, 2019; Rommel et al., 2018; Karunathilake et al., 2018; Koirala et al., 2016; Bauwens, 2016; Schoor et al., 2016; Dóci et al., 2015). In turn, the integration of electricity, heating and transport sector together with community engagement is expected to contribute to more flexible, cost effective and efficient local energy systems (Koirala et al., 2016; Thellufsen and Lund, 2016). In this regard, energy communities are a modern development to re-organize the energy system to simultaneously integrate distributed energy resources and engage local communities (Bauwens and Devine-Wright, 2018; Koirala et al., 2016).
On the other hand, policies that have boosted the development of local renewable projects are being withdrawn across several European countries, including pioneers like Denmark and Germany, where shifts from feed-in tariffs to more market-based instruments have progressively taken place (Bauwens et al., 2016; Leiren and Reimer, 2018; Lundberg, 2019). This has led energy communities to become increasingly professional and commercial and to search for new business models. This has notably involved a diversification of their revenue streams by proposing other offerings on the top of renewable energy generation, for example electric mobility services, energy efficiency models and demand side management (Funkhouser et al., 2015; Gui and MacGill, 2018; Herbes et al., 2017; Mirzania et al., 2019). Another notable evolution is the emergence of networks, intermediaries, coalitions and collaborative dynamics among initiatives, which help existing and aspiring communities with various aspects of project development and advocacy work (Bauwens et al., 2019; Hargreaves et al., 2013; Huybrechts and Haugh, 2018).
These changes in policies and business models will likely have consequences on the forms of, and motivations behind, participation in energy communities. Until recently, energy communities were driven by environmentally or socially motivated collectives of citizens willing to collaborate, share benefit and challenge incumbent energy systems (Bauwens, 2016; Koirala et al., 2018a; Rogers et al., 2008; Wirth, 2014). It remains to be seen how these policy changes and these evolutions in business models will affect the dynamics of community engagement. Similarly whether, these new networks and intermediary organizations will be able to ensure the inclusion of a broader diversity of communities is an open question.
This special issue in Sustainabilty will focus on the process aspects of the ongoing energy transition by contributing to knowledge acquisition on how these changing policy and technological landscapes affect energy communities in terms of conditions for emergence and development, motivations and social dynamics of collective action and participation business models, energy system integration options, local energy market design, policy and regulatory issues, socio-technical configurations and community engagement. In this context, this special issue invites interdisciplinary contributions on technological, socio-economic and institutional aspects of energy communities as well as their roles on the ongoing energy transition.
We invite manuscripts on following (not limited) topics:
- Local, virtual and hybrid energy communities
- Positive energy districts and neighborhoods
- Energy communities as commons
- Opportunities for and challenges to energy communities
- Enabling technologies and digitalization
- Techno-economic and socio-institutional assessments of energy communities
- (Self-) governance, ownership, business models, cost-benefit allocations
- Polycentricity, meta-governance, and policy-mix approach for energy communities
- Design of local energy markets
- Demand response and flexibility in energy communities
- Intrinsic motivations and drivers for energy communities
- Energy system integration and role of multi-energy carriers (electricity, hydrogen, heat)
- Socio-technical innovations and alignments
- Citizens and community engagement
- Regulation and legal frameworks for energy communities
- Changing roles and responsibilities
- Multi-actor perspectives on energy communities
- Energy communities and local/regional energy transition
- Energy Citizenship
- Digital twins of energy communities
Keywords: Community energy, community engagement, renewable energy, energy transition, peer-peer energy exchange, business models, institutional design, energy citizenship, (self-) governance, socio-technical innovation
Guest editors:
Binod Koirala
David Parra
Thomas Bauwens
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Dear Binod Prasad Koirala
Thank you for your invitation to participate in this issue.
The only problem with MDPH publications is the high publishing fees. I hope these publishers will reduce or exempt researchers from some of these fees so that they can publish their valuable research.
Best regards
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What are the impacts of applying information technology for optimizing resources (farming, smart grid)?
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I have many monographs and scientific articles on this subject, but they are in Russian:
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Hi,
For balanced three-phase electrical signals, the Clarke transform is a well-proven technique for dimensional reduction. Indeed, this transform can project the information from a 3D space to a 2D space without any loss of information. For sinusoidal balanced signal, the projected signal describes a circle in the projected plane (see the first attached image). This simplifies the frequency estimation since the circle simply corresponds to the analytic signal.
Now, for unbalanced system, the use of the Clarke preprocessing is quite questioning. Indeed, for unbalanced sinusoidal signals, the signal describes a circle in a particular plane (which is not the same that the one obtained for balanced systems). By using the Clarke transform, the projected signal describes an ellipse instead of a circle (see the second attached image) and the projection will inevitably loss some kind of information. This makes the frequency estimators suboptimal regarding the information contained in the three phases. From my point of view, this makes the Clarke transform inappropriate for the analysis of unbalanced three-phase signals.
In this context, I don’t know why many papers still use the Clarke transform for dimensional reduction in unbalanced three-phase systems ?
References:
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Not sure if you are still looking for an answer to this question, but the Clarke transformation does not loose any information, even for unbalanced systems. You can easily prove that the Clarke transformation is an isomorphism, thus there is no loss of information.
Of course, what many people do for many reasons is omitting the zero sequence. Then you are loosing information in an unbalanced system...
The big advantage is that this transformation converts abc quantities into an orthogonal space. With that you eliminate a lot of cross-couplings terms in the system equations (i.e. more zeros appears in the off diagonal terms of matrices).
By the way, the Clarke transformation is the basis for the p-q power theory that is used in the control loops of converters exactly for unbalance compensation.
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Basically I get many research paper where are different types of metaheuristic algorithms used in the smart grid or the smart microgrid operation for optimization. I just want to know which algorithms are essential to optimize smart grid operation.
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This largely depends on your design problem. What aspect of smart grid operations do you want to optimize? What are your constraints criteria? Remember, smart grid operations is very wide. So, your design architecture dictates which optimization tool is applicable.
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Hi,
Can anybody please suggest me if there are open access data for the cyber security specially for energy delivery systems or smart grid systems? If there are data from PMU or testbeds that would be very helpful. I want to use the data only for my model developing purpose for my PhD work.
Thanks,
Md Ariful Haque
PhD candidate,
Computational Modeling and Simulation Engineering,
Old Dominion University
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First of all, Smart Grid covers the power generation, transmission and distribution. But, the most considerable change happens in distribution level, where we have customers (houses, buildings, schools, factories,..).
Now a day, utility companies send you the electricity via the distribution lines. There is no feedback from you to them! It’s like one way road. In Smart Grid customers are connected to the utility companies and even to other customers. They talk and control power grid together. We call it demand response.
Moreover, Smart Grid makes facility to have more renewable energy sources like Solar and Wind. We are going to improve green energies and system efficiency! It’s just a big picture....
I suggest you to take a look to this document from Department of Energy:
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What’s your question?
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How to the optimization of smart grid operation using a soft algorithm?
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You can use optimization tool in the matlab environment.
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Where can I find and study about the Narrow Band IoT?
Provide me with papers link and documents' link...
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A follow-up comment: looking at the family of cellular IoT (EC-GSM-IoT, LTE-M and NB-IoT), NB-IoT provides the biggest deployment flexibility. Note that EC-GSM-IoT was designed to reuse GSM infrastructure and frequency channels (200kHz bandwidth); around 300-400kbps data rates are possible, but the activity around it in the industry and academia is rather limited, to my best knowledge. On the other hand, LTE-M is to be deployed in-band with LTE, uses wider bandwidth (6 PRB) and provides higher data rates (ideally up to 1Mbps). Finally, NB-IoT is the slowest (data rates no more than ~200kbps), but it only needs 1PRB (180kHz) to operate, meaning that one can either reuse a GSM carrier for it (still preserving 10kHz guardbands), place it in-band with LTE or even allocate NB-IoT within the LTE guardband.
I think the following book is the great source of knowledge:
Olof Liberg et al. "Cellular Internet of Things: Technologies, Standards, and Performance".
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I'm working on micro-grids and V2V energy transmission controlled by the blockchain. Kindly help me regards simulation tools that can help in this research work.
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Dear Hamza,
could you be more specific? do you need some works on the field? Or do you have a precise model you want to simulate?
Regards,
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Suppose voltage, current and frequency data can be accessed from different points in the power distribution networks. What are the various problems that DSOs face and can be solved with that data? I would specially like to receive inputs from the persepective of European grids.
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This is a very interesting question. From my experience with German DSO's, a topic that always comes up is related to data acquisition (metering and monitoring) at the LV level. This as we understand is the basis for several more challenges such as accurate model validation for LV distribution and micro-grid operation. The norm is that distribution grid planning does not involve detailed analysis in most cases and usually it is only based on some worst case scenarios. This leads to often a very oversized network. Lack of data also means, we are not able to accurately predict certain behaviors of the LV network that may arise in the future as a result of growing DER expansion. This is one of the biggest challenges to fast-forward energy transition at urban scale.
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Hello,
Currently one can estimate the ageing cycles (charge+discharge) of EV. Does anyone know how much is the cycle is vehicle2grid facility is introduced ? This number can be for any EV as example.
Any links/references will be useful.
Thanks,
Praveen
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EV to Grid can work beyond 30 yrs for electrical system comparision to 12 yrs of fuel engine life.
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Hello,
Does anyone know the cost to install Vehicle2grid service at home or commercial places ? I found a rough price as 5000$ in internet, but could anyone recommend a much cheaper solutions or upgrade cost from unidirectional to bidirectional (Electric vehicle <---> grid) ?
I would like to know in details the installation cost. Any links/references will be useful.
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I'm interested
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I am looking for modified IEEE distribution test systems with microgrids/DERs.
Can anyone help me with this?
Any distribution test systems with MGs /DERs will be appreciated.
Thanking you very much.
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I am curious if the current electricity pricing mechanisms are suitable for a grid with distributed renewable generation. I am interested in real-time pricing where changes in demand and renewable generation determines the price. Can we use a mechanism e.g. Price = m x Pi + Price_base where Pi is power injection on a bus i.e. difference in generation and load, Price_base is the base price settled in day-ahead market and m is the rate at which the price is increased to achieve demand response.
I am a newbie, have studied number papers but so far none I could find that deals with distributed generation.
Any helpful guidance would be great.
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What are you trying to achieve here? Let's be clear by what you mean by price. Is it the price on some network, or the price paid by the consumer? Surely not the latter as that is determined solely by how much profit the reseller wants to achieve and has nothing to do with spot pricing. Since the generation cost of the electricity doesn't change from moment to moment, you are surely trying to derive, in this 'price', and economic signal on which some further decisions are based. What sort of signal, what sort of decisions do you anticipate being made? Then you will be able to determine how to generate a suitable economic signal for them. But as you can see, I am VERY sceptical about all this sort of thing; I am disgusted at finding the consumer price of electricity is likely 8 or 10 times its generation cost and has nothing to do with any spot price however derived at some point in the transmission / distribution chain.
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I need suggestions for research in smart grid...
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Demand side management of power can be a good area of research in smart grid application for developing and underdeveloped countries
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Dear modern power distribution network planners and researchers, do you have a summary in mind that presents the main challenges of modern power distribution networks?
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As a person who worked in an electricity distribution company about 20 yesrs, these are the most important challenges in the future electricity distribution companies :
1- Load mobility and challenges of dist. sys. design
2- Mercury Contamination of CFLs and recycling.
3- Vibration and its effects on forming of Loose Connections
4- Air pollution , harsh environment and their effects on insulators
5- Fast switching devices and their related voltage kicks
6- The need for designing more compact equipments
7- Challenges of big data collection and analysis
8- Cyber sequrity
9- EMC and decreasing the gap between immunity level of loads and disturbance level of network
10- Protection of active distribution networks and microgrids
11- Distribution sys aging
12- Electricity demand growth
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When move discuss about the power quality problem in smartgrid, what are the possibilities and available techniques for improvement of power quality.
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Power quality improvement in presence of RESs
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Vehicle to grid technological scheme for grid integration is an emerging trend in smart grid technology.
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-Application of V2G to improve system frequency
-Smart homes with V2G
-Power quality issues with V2G
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