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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!
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会议征稿:第四届智能电网与能源互联网国际会议(SGEI 2024)
Call for papers: IEEE 2024 4th International Conference on Smart Grid and Energy Internet (SGEI 2024) will be held during December13-15, 2024 in Shenyang, China. SGEI 2024 is hosted by Shenyang University of Technology.
Conference website(English): https://ais.cn/u/bIbYNn
重要信息
大会官网(投稿网址): https://ais.cn/u/bIbYNn
大会时间:2024年12月13-15日
大会地点:中国-沈阳
收录检索:IEEE Xplore,EI Compendex,Scopus
会议详情
由沈阳工业大学主办的2024年第四届智能电网与能源互联网国际会议(SGEI 2024)将于2024年12月13日至15日在中国沈阳举行。会议主要围绕智能电网与能源互联网等研究领域展开讨论。旨在为智能电网与能源互联网等领域的专家学者及企业发展人提供一个分享研究成果、讨论存在的问题与挑战、探索前沿科技的国际性合作交流平台。本次会议将大力推广能源领域的创新技术和实际应用,旨在充分实现各类能源资源的互联、开放、共享和协同,塑造绿色、低碳、高效和低成本的智慧能源系统。大会诚邀国内外高校、科研机构专家、学者,企业界人士及其他相关人员参会交流。
征稿主题(包括但不限于)
分布式能源:可再生能源和存储,微电网和虚拟电厂,电力电子和电网接口,能源和配送管理系统,能源系统的监测,保护和控制,智能电网技术,能源转换和存储  ,传输系统技术,HVDC和FACTS,配电系统和变电站自动化,智能电网的信息和通信技术,监测和控制智能电网的电能质量,多领域应用的智能电网,电源质量、保护和电磁兼容性,电力工程发电技术,电动驱动器及其应用,大电网稳定控制,电力系统通信与控制,电网智能调度,能源互联网的建模、仿真与设计,人工智能技术,智能配用电与微电网,能源互联网的装备核心技术,直流电网,物联网,支撑能源互联网的信息物理系统及信息安全,全球能源互联网,能源效率,能源战略与能源互联网 ,新能源系统及控制等。
论文出版
SGEI 2024投稿,都必须经过2-3位组委会专家审稿,经过严格的审稿之后,最终所有录用的论文将由IEEE(ISBN:979-8-3503-6831-4)出版,见刊后由出版社提交至IEEE Xplore, EI, Scopus检索。
报名参会:
1、作者参会:一篇录用文章允许一名作者免费参会;
2、主旨报告:可申请主题演讲,由组委会审核;
3、口头报告:可申请口头报告,时间为10分钟;
4、海报展示:可申请海报展示,A1尺寸,彩色打印;
5、听众参会:不投稿仅参会,也可申请演讲及展示;
6、报名参会:https://ais.cn/u/bIbYNn
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Interesting
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2025 4th International Conference on Smart Grid and Green Energy (ICSGGE 2025) February 28th – March 2nd, 2025 University of New South Wales, Sydney, Australia Technically Co-sponsored by IEEE & IEEE New South Wales Section Organizer: School of Information Systems and Technology Management, UNSW Co-organizers: Hainan Institute of Zhejiang University, Sanya Global Energy Research Institute, AEIC Academic Exchange Information Center Media Supporter: <Energy Conversion and Economics> Official Website: https://ais.cn/u/Rzqi6r The University of New South Wales is honored to host the 4th International Conference on Smart Grid and Green Energy (ICSGGE 2025). Set against the backdrop of vibrant Sydney, Australia, this prestigious conference invites researchers, scientists, engineers, and scholars from around the world to converge for an enriching exchange of insights from February 28th to March 2nd, 2025. Objective: ICSGGE 2025 aims to serve as a distinguished platform for the presentation and discussion of innovative research in the domains of Smart Grid and Green Energy. We are dedicated to fostering a collaborative environment that promotes the exchange of experiences, pioneering ideas, and practical solutions to challenges faced in the evolution of sustainable energy systems. Call for Contributions: We invite the submission of original research papers, case studies, and reviews that address various aspects of Smart Grid and Green Energy, including but not limited to: Advanced smart grid systems, technologies, and methodologies Renewable energy integration and energy storage solutions Energy efficiency and demand-side management Power system management, control, and stability Sustainable and intelligent energy policies Cybersecurity and privacy in smart grid technologies Data analytics and machine learning applications in energy systems Emerging trends in green energy and smart infrastructure
Submission Guidelines: Authors are invited to submit manuscripts electronically in accordance with the guidelines outlined on the conference website. All submissions will undergo a rigorous peer-review process to ensure the highest standards of quality and relevance. Publication: Accepted papers will be published in the IEEE Xplore Digital Library and will be indexed by EI COMPENDEX and SCOPUS, providing significant visibility and outreach to the broader academic and professional communities. Important Dates: Submission Deadline: January 24, 2025 Notification of Acceptance: Februry 1, 2025 Camera-Ready Submission: Februry 21, 2025
Join us at ICSGGE 2025 to share your knowledge, explore groundbreaking advances, and contribute to the transformative discussions shaping the future of Smart Grid and Green Energy. For more details, please visit the conference website:
We eagerly anticipate your contributions and look forward to welcoming you to an academically stimulating and enlightening conference in Sydney!
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Tawfiqullah Muradi Please send the full paper(word+pdf) to Submission System:https://ais.cn/u/Rzqi6r
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Does the EU smart grid strategy empower consumers to actively participate in the energy transition through demand response programs, energy management solutions, support for prosumer participation, and consumer awareness initiatives for meeting climate change mitigating goals? As a follow-up question, does it give the EU electricity customers greater visibility, control, and incentives to manage their energy usage efficiently? In turn, does the EU aim to harness the collective efforts of households and businesses to achieve a more sustainable and resilient energy system? Kindly comment.
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Applying system dynamics to business model innovation for digital transformation has the potential to be of great value, enabling a deep understanding of the behavior of complex systems and optimized decision-making. However, the key to success lies in effective data management, cross-department collaboration and continuous model updates to overcome complexity and implementation barriers. By properly addressing these challenges, companies can achieve sustainable business model innovation in a dynamic market environment.
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Fairness is a very important factor during the application of DR programs. The implementation of a DR program which provides a fairness would encourage customers participation. Thus, more participations would boost effectiveness of the DR program. So, what are the fairness indices which are used in demand side management studies and how they can be measured or calculated?
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Equity is a key factor in the success of demand-side management projects. Through the combined use of quantitative and qualitative methods, the fairness of participation of different groups in DSM projects can be effectively measured and evaluated. This not only helps improve customer engagement, but also ensures that policy implementation is equitable and effective, thereby advancing the achievement of the Sustainable Development Goals.
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IEEE 2024 8th International Conference on Electrical, Mechanical and Computer Engineering (ICEMCE 2024) will be held on October 25-27, 2024 in Xi'an, China.
Conference Website: https://ais.cn/u/baUBfa
---Call for papers---
The topics of interest for submission include, but are not limited to:
· Smart grid
· Heat exchanger
· Computer simulation
· Artificial intelligence (AI)
· Computer modeling
· Mobile computing
· Instruments and meters
· Power and fluid machinery
· Heat and mass transfer
· Laser processing technology
· Wireless sensor networks
· Electric energy processing
· Electromagnetism and photonics
· Power quality and system stability analysis
· Photoelectric effect of semiconductors
· Refrigeration and air conditioning
......
---Publication---
All accepted papers will be submitted to IEEE (ISBN: 979-8-3315-0623-0) for publication, and it will be submitted to IEEE Xplore, EI Compendex and Scopus for indexing.
---Important Dates---
Full Paper Submission Date: September 30, 2024
Registration Deadline: October 18, 2024
Final Paper Submission Date: October 18, 2024
Conference Dates: October 25-27, 2024
--- Paper Submission---
Please send the full paper(word+pdf) to Submission System:
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I'm interested...
I would appreciate any information regarding key dates. And to know how much is involved.
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How to use and this is economical?
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Smart grid mainly use computers online applications with interfaced controllers for instrumentation, protection and control, which provides faster instrumentation protection and control than the normal hence system efficiency and reliability could be optimized for the working system load angle within stability would provide higher active power with less reactive power. The computerized load dispatch center connected to all generating stations allows load distribution in most economical ways, with optimized the solar and wind power in systems, the developed microprocessor based load shedding controllet with microprocessor based loads optimization are discussed in my papers……
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IEEE 2024 5th International Conference on Clean Energy and Electric Power Engineering (ICCEPE 2024) will be held in Yangzhou City, Jiangsu Province, China on August 9-11, 2024.
Conference Website: https://ais.cn/u/3yQnau
---Call for papers---
The topics of interest include, but are not limited to:
◕ Clean energy
(1) Renewable energy technologies and systems
(2) Renewable energy storage technology
(3) Energy efficiency
(4) Solar thermal energy
(5) Solar seawater desalination
......
◕ Power Engineering
(1) Electric power allocation
(2) Power flow analysis
(3) Power quality
(4) Cogeneration and distributed generation
(5) Power system and energy
......
◕ Smart Grid and Energy Science
(1) Distributed generation and combined generation system
(2) Energy management and environmental issues
(3) Hybrid power system
(4) Hydraulic power plant
(5) Hydrogen system and fuel cell
......
---Publication---
All papers, both invited and contributed, the accepted papers, will be published in IEEE(ISBN: 979-8-3503-9031-5) and submitted for inclusion into IEEE Xplore subject to meeting IEEE Xplore's scope and quality requirements, and also submitted to IEEE Xplore, EI Compendex and Scopus for indexing. All conference proceedings paper can not be less than 4 pages.
---Important Dates---
Full Paper Submission Date: June 24, 2024
Registration Deadline: July 25, 2024
Final Paper Submission Date: August 5, 2024
Conference Dates: August 9-11, 2024
--- Paper Submission---
Please send the full paper(word+pdf) to Submission System:
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Thanks Kiuling Lai, I have contacted the secretary but no response from my email till now. Still waiting for the acknowledgement of my email.
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2024 8th International Conference on Energy Technology and Materials Science(ICETMS 2024) will be held in in Chongqing, China from May 31 to June 02, 2024.
ICETMS 2024 will provide unique opportunity to have fruitful discussions about Energy Technology, Material Science, Power Electronics, Systems and Applications, and best practices that address industrial challenges. The event includes large number of speakers and quality papers that cover energy generation, transmission and distribution infrastructures, energy storage and Material.
---Call For Papers---
The topics of interest for submission include, but are not limited to:
Track 1: New Energy Technologies and Renewable Energy Sources.
1. New and Renewable Energy Technologies
2. Photovoltaics, Photocatalysis and Solar Energy
3. Energy conversion and storage materials
4. Energy Management and Smart Grid
5. Traditional energy transformation and cleaner production
6. Low-carbon technologies and carbon capture and storage
7. Materials Science and Engineering in Energy Technology
8. Energy security and sustainable development
9. New energy materials and material design
10. Energy system simulation and optimization
Track 2:  Energy Storage Technologies and Battery Materials.
1. Energy storage technologies and battery materials
2. Fuel cells and hydrogen energy
3. Renewable energy and power systems
4. Energy efficiency and energy saving technologies
5. Wind and ocean energy
6. Synthesis and preparation of energy materials
7. Application of materials science in energy technology
All accepted papers will be published in the Journal Of physics: Conference Series (ISSN:1742-6596), and it will be submitted to EI Compendex and Scopus for indexing.
Important Dates:
Full Paper Submission Date: April 20, 2024
Registration Deadline:May 10 , 2024
Final Paper Submission Date: May 20 , 2024
Conference Dates: May 31-June 02, 2024
For More Details please visit:
Invitation code: AISCONF
*Using the invitation code on submission system/registration can get priority review and feedback
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Thank you for the information
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Optimization by genetic algorithm (GAO) in electricity and smart grid?
why we use it ?
what is the process of this algorithms ?
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Genetic Algorithms (GAs) are heuristic algorithms widely used for performing optimization especially in complex systems. Indeed, in those circumstances, finding the exaxt solution to the problem at hand could be very hard because of lack of information or mathematical issues. Smart Grids (SGs) are basically groups of modular interconnected electrical grids with many nodes (e.g. residential buildings) and elements (e.g. batteries and PV generators), generally aimed at reaching the minimum operative costs for their users. Therefore, energy flows between nodes have to be optimized with the aforementioned purpose. To sum up, GA optimization is useful for SGs since they are complex systems to be optimized.
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2024 International Conference on Smart City and Information System (ICSCIS 2024) will be held in Kuala Lumpur, Malaysia from May 17-19, 2024.
---Call For Papers---
The topics of interest include, but are not limited to:
1. Smart City
- Smart Grid
- Smart Manufacturing
- Wireless Communication
......
2. Information System
- Information Systems and Security
- Information Management Systems
- Internet of Things (IoT)
......
3. Other Related Topics
All accepted full papers will be published on Conference Proceedings and submitted to EI Compendex and Scopus for indexing.
Important Dates:
Registration Deadline Date: May 8, 2024
Final Paper Submission Date: May 13, 2024
Conference Date: May 17-19, 2024
For More Details please visit:
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Thank you so much
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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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𝟯𝗿𝗱 𝗜𝗻𝘁𝗲𝗿𝗻𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗖𝗼𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝗼𝗻 𝗘𝗹𝗲𝗰𝘁𝗿𝗶𝗰𝗮𝗹, 𝗣𝗼𝘄𝗲𝗿 𝗮𝗻𝗱 𝗚𝗿𝗶𝗱 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 (𝗜𝗖𝗘𝗣𝗚𝗦 𝟮𝟬𝟮𝟰) 𝘄𝗵𝗶𝗰𝗵 𝘄𝗶𝗹𝗹 𝗯𝗲 𝗵𝗲𝗹𝗱 𝗶𝗻 𝗞𝘂𝗮𝗹𝗮 𝗟𝘂𝗺𝗽𝘂𝗿, 𝗠𝗮𝗹𝗮𝘆𝘀𝗶𝗮. 𝗼𝗻 𝗝𝗮𝗻𝘂𝗮𝗿𝘆 𝟮𝟲-𝟮𝟴, 𝟮𝟬𝟮𝟰.
---𝐂𝐚𝐥𝐥 𝐅𝐨𝐫 𝐏𝐚𝐩𝐞𝐫𝐬---
The topics of interest for submission include, but are not limited to:
· Solar Power
· New Energy Power Generation
· Transmission of Electrical Energy
· Signal and System
· Power Systems and Automation
· Electrical System Modeling
· Power System Communication and Control
· Computational Intelligence in Electrical Engineering
· Electrical Materials and Equipment
· Power System Protection and Control
· High Voltage and Insulation
· Smart Grid
· Microgrid
· Smart Sensors
· Smart Networks and Communications
· Materials for Electrical and Optoelectronics
· Machine Learning and Artificial Intelligence in Power Systems
· Big Data Application in Power Systems
All accepted papers will be published in the Conference Proceedings, and submitted to EI Compendex, Scopus for indexing.
𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐃𝐚𝐭𝐞𝐬:
Full Paper Submission Date: December 10, 2023
Registration Deadline: December 30, 2023
Final Paper Submission Date: January 12, 2024
Conference Dates: January 26-28, 2024
𝐅𝐨𝐫 𝐌𝐨𝐫𝐞 𝐃𝐞𝐭𝐚𝐢𝐥𝐬 𝐩𝐥𝐞𝐚𝐬𝐞 𝐯𝐢𝐬𝐢𝐭:
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Usman Anka Abdulaziz Yes,the conference's Final Paper Submission Date is before January 12, 2024.
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Hello, I am currently writing a paper that reqires me to simulate a renewable energy grid with machine learning. I'd be grateful if anyone with experience on this can give a few suggestion as to which software to use for this task. Thanks in advance.
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try this one: https://pypsa.org/
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What are the techniques used to detect, identify, localize the faults in microgrid/smart grid/ active distribution grid using Phasor measurement unit?
Please explain about the techniques about the restoration of system after the abnormalities occurred in the power networks specially in DGs
Thank you
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Dear Doctor
Go To
Micro Phasor Measurement Units: a Review from the Prosumer Point of View F. Ciancetta , A. Fioravanti , E. Fiorucci , Simone Mari , A. Prudenzi1 and A. Silvestri
21 th International Conference on Renewable Energies and Power Quality (ICREPQ’23) Madrid (Spain), 24 th to 26 th May 2023
"Abstract.
In recent years, power grid infrastructure has moved from a centralized power generation model to a paradigm in which generation capacity is distributed across an increasing number of small power plants that rely on renewable energy sources. Systems for emerging distribution systems need a very new protection paradigm, architecture and philosophy making use of new protection devices and sensors such as digital relays, phasor measurement units (PMUs), smart reclosers and line sensors. This article examines the application of PMUs in smart distribution grids and from the point of view of prosumers.
Conclusion
PMU applications still face many challenges in distribution systems, such as inadequate phasor measurement accuracy and the lack of a communication network infrastructure that can support a large number of sensors and actuators with different technologies, but also advanced and persistent cyberthreats facing critical infrastructures such as the intelligent grid are also exponentially increasing and require a sophisticated defense strategy. In addition to RES and electrical energy storage, active loads such as demand-responsive loads and electric vehicles will also increase. All these factors introduce new challenges in the operation, planning, protection and control of distribution grids. The communication systems used and the pmu calculation algorithm will have to face the growing challenges of modern networks; therefore they will have to be increasingly robust and reliable. This article presents a review of the phasor unit of measurement applied to distribution grids that will radically change in this decade. Above all attention was given to its working principle and the various applications in this context. For detailed analysis, the appropriate references have been cited."
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I have to used IEC-61850 communication protocol used for substation automation through OPAL-RT?
I know its working and i have also verified my results through OPAL-RT but there is some problem i am having in case of its block diagram, that how i will introduce its components of working in my normal block diagram?
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Dear Alok Jain
I apologize for my previous response in which I referred to you as a student. What I meant to say was that your students and yourself were waiting for a response, and I am unsure why you did not receive one. Upon seeing this, I felt compelled to reply.
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Hi, I am using appliance scheduling on a particular day using optimization techniques. Can I perform economic evaluation of solar PV systems integrated with smart grid using HOMER Grid software.
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Yes, it is possible to perform economic evaluation of solar PV systems integrated with smart grid using HOMER Grid software. HOMER Grid is a software that models and optimizes the design of hybrid renewable energy systems, including solar PV, wind, and battery storage, as well as their integration with the grid.
HOMER Grid's optimization feature allows users to model different scheduling strategies for appliances, taking into account factors such as load profile, electricity rates, and battery storage capacity. It generates an optimal system design and operation strategy that minimizes the overall system cost, including the cost of the renewable energy system, electricity purchases, and maintenance.
The software also provides a detailed economic analysis of the hybrid renewable energy system, including the levelized cost of energy (LCOE), net present value (NPV), and return on investment (ROI). This allows users to evaluate the economic feasibility of the system and its potential for cost savings over time.
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Cloud Computing, Big Data, IoT
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A mechanism to defend attacks based on the Training Data might be of interest. You might find the article below relevant, and it has some interesting references you might want to contact.
This is a very hot topic right now.
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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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Nz Kh could you please share the links such datasets?
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Can we model an information system to create a sync between different power generation units to generate power in most economic way based on current weather condition?
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I think most utility scale energy management systems have been able to do this for many years. Load can be estimated on a combination of historical data and current weather forecasts such as temperature and cloud cover.
The total load demand can then be used in an economic dispatch application to allocate the most economic generation (including virtual power plants).
As Samir mentioned, the big challenge is to how to prepare the data models.
These have to link the loads, typically defined according to the electrical network, with the weather forecasts, typically available in squares of several 10s of km.
Historical data can be used to make the correlations or train AI but this is now more complicated as the number of solar panel installations grows every year.
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Understanding and predicting the complex or chaotic behaviors of complex and nonlinear systems is very interesting and challenging, especially when we deal with it in practical systems, like smart city or energy systems It turns out that complexity and chaos theories may provide us with a framework to explore these. Complexity in energy systems involve multiple factors, such as weather changes, unseen failures, demand, energy prices, and consumer behavior, which can exhibit unforeseen behaviors like emergence that are difficult to predict.
What is your opinion on the link between Complexity and Chaos Theories, and energy systems, which concerns the following questions:
  • Can complexity and chaos theories be used to better understand and predict the behavior of energy systems?
  • What challenges and limitations do we face when applying complexity and chaos theories to energy systems?
Recent studies have explored the use of computational techniques, such as machine learning and entropy-based information theoretical methods, to analyze complex systems and identify chaotic behavior. For example, one study proposed using complex system characteristics as features for time series data to identify chaotic behavior, achieving high precision on test data [1]. Another study explored the use of deep learning methods for classifying chaotic time series, achieving an impressive accuracy of 99.45 percent on unseen samples [2]. A third study utilized entropy-based methods to develop an effective approach for classifying time-series data [3].
Join us in this discussion and share your thoughts on how we can use complexity and chaos theories, as well as and other computational techniques to better understand and predict the behavior of complex systems in energy systems, and the like. Let's explore the potential of these methods and discuss the challenges and limitations we face in applying them to real-world energy systems.
References:
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Picture belongs to Ref. 3 of the Discussion.
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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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Anything related to converters, Charging, and EVs to Smart Grid.
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dispatching of EVs, considering the price and psychology of using electricity to model the charging/discharging of EVs, then put it into DSO to have the whole dispatching
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As I mentioned above reviewer has asked me to make changes, like write down complete details about faults in the smart grid though my paper is about faults in transmission lines. My paper already has 12 pages if I add those irrelevant details it will increase the number of pages also. And another thing he has asked to merge all graphs which I think will make it too much complicated for reading. So how should I deny those changes which will not a kind of "offened" the reviewer?
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Just try to do everything the reviewer asks because it will make the process easier :)
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I need a project topic on smart grid technology. please help.
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there are many of interdisciplinary nature in Smart Grid development and depending on your major you can select whichever is suitable to you. For instance, if your major is in Communication, you may look at the type of communication network suitable for particular applications areas of Smart Grids, such as smart metering. this is just one example, and you can add more and more examples depending on your area of interest.
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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 description of how something works using four types of things: Place, Transition, Input and Output. Each thing is a net element or element: a place, a transition, an input and an output. An input connects a place to a transition. An output connects a transition to a place. A Petri Net can be shown as a diagram. It can also be created as using a diagram. The diagram may use a shape for each net element: a place as a circle, a transition as a square, an input as an arrow from a circle to a square and an output as an arrow from a square to a circle. Other types of shapes can be used such as an ellipse instead of a circle or a rectangle instead of a square. The diagram may use a shape for more than one net element; in this case the diagram is a special type of high level Petri Net diagram.
A Petri Net diagram is more than the shapes found in it. The elements represented by the diagram have tags (also called annotations or inscriptions). The tags and their values may be visible or invisible from the Petri Net diagram.
What is a Petri Net? A Petri Net is a description of how something works using net elements and tags.
A PDF version of this reply is available at https://www.researchgate.net/publication/361783820_Petri_Nets_an_Explanation_A_Reply_to_What_is_a_Petri_Net_at_the_Question_Forum_of_ResearchGate. It includes two examples of interactive Petri Net diagrams, one figure with visible tags, one figure with visible tags and tag values and an attachment (an HTML version of the PDF version).
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5G generates environmental problems due to the high consumption of mobile networks and radio technologies uses. How can renewable energy and smart energy grids contribute to this problem? Any specific paper? I know thousands. Any special? Thank you in advance.
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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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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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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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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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(1) Connecting building, building-integrated renewables and waste energy and mobility sectors. Think beyond e-cars, e.g. commercial micromobility docks, or even public transport on larger scale.
(2) Design commercial entities that are like ESCO-s for the carbon market. The upcoming ETS expansion will include buildings and mobility fuels, dig into how it works and come up with a model that can reap the benefits.
(3) Thermal smart grids, 5th generation district heating/cooling microgrids.
(3) Pogram energy communities, which can have a los of use-cases (For more info:
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Smart grid stability isssues and prediction of instability using Machine learning techniques
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I think these papers could help you;
  1. Stability Concerns in Smart Grid with Emerging Renewable Energy Technologies, February 2014,
  2. Impact of Distributed Generation on Smart Grid Transient Stability, January 2011,
They're available on the ResearchGate Server for download.
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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 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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Somepne please help me where to learn the simulation of Smart Grid on YouTube or other bookr esources?
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Thanks Adnan Anwar
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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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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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Computer files could be transferred in no time of few seconds with in world.....
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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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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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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.