dc.contributor.author |
Saini, Vikas K.
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|
dc.contributor.author |
Kumar, Rajesh
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|
dc.contributor.author |
Sujil, A.
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|
dc.contributor.author |
Bansal, Ramesh C.
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dc.contributor.author |
Ghenai, Chaouki
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dc.contributor.author |
Bettayeb, Maamar
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|
dc.contributor.author |
Terzija, Vladimir
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dc.contributor.author |
Gryazina, Elena
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dc.contributor.author |
Vorobev, Petr
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dc.date.accessioned |
2025-03-19T10:20:29Z |
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dc.date.issued |
2024-12 |
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dc.description |
DATA AVAILABILITY : No data was used for the research described in the article. |
en_US |
dc.description.abstract |
Smart grid can offer load sharing and utilize distributed energy resources to reduce energy consumption costs and potentially earn revenue through energy services. Information and communication technologies (ICT) in the smart grid have opened a lot of possibilities for developing residential Demand Response (DR), which is essential in smart grid applications. DR is a technique that enables customers to participate in the operation of the electricity grid either by shifting or reducing the loads during peak time in response to price signals. The DR program helps utilities ensure power balance and lower the cost of electricity in both wholesale and retail electricity markets. Multi-Agent System (MAS) is a distributed artificial intelligence technique that can be used for the implementation of DR programs in the electricity market. This paper aims to provide a comprehensive review of the MAS application for the implementation of DR programs in electricity markets. This paper highlights a review of 264 research papers that discusses MAS-based DR, MAS-based DR in the electricity market, and various platforms for the development of MAS-based DR. It also summarizes the potential of MAS in other applications of the smart grid along with the MAS research challenges, benefits, constraints for implementation and future research directions in this field. |
en_US |
dc.description.department |
Electrical, Electronic and Computer Engineering |
en_US |
dc.description.embargo |
2026-11-23 |
|
dc.description.librarian |
hj2024 |
en_US |
dc.description.sdg |
SDG-07:Affordable and clean energy |
en_US |
dc.description.sdg |
SDG-09: Industry, innovation and infrastructure |
en_US |
dc.description.uri |
http://www.elsevier.com/locate/segan |
en_US |
dc.identifier.citation |
Saini, V.K., Kumar, R.,Sujil, A. et al. 2024, 'Multi agent framework for consumer demand response in electricity market : applications and recent advancement', Sustainable Energy, Grids and Networks, vol. 40, art. 101550, pp. 1-24, doi : 10.1016/j.segan.2024.101550. |
en_US |
dc.identifier.issn |
2352-4677 (online) |
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dc.identifier.other |
10.1016/j.segan.2024.101550 |
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dc.identifier.uri |
http://hdl.handle.net/2263/101601 |
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dc.language.iso |
en |
en_US |
dc.publisher |
Elsevier |
en_US |
dc.rights |
© 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. Notice : this is the author’s version of a work that was accepted for publication in Sustainable Energy, Grids and Networks. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in Sustainable Energy, Grids and Networks, vol. 40, art. 101550, pp. 1-24, doi : 10.1016/j.segan.2024.101550. |
en_US |
dc.subject |
Smart grid |
en_US |
dc.subject |
Multi-agent systems |
en_US |
dc.subject |
Demand response |
en_US |
dc.subject |
Energy market |
en_US |
dc.subject |
Information and communication technology (ICT) |
en_US |
dc.subject |
SDG-07: Affordable and clean energy |
en_US |
dc.subject |
SDG-09: Industry, innovation and infrastructure |
en_US |
dc.title |
Multi agent framework for consumer demand response in electricity market : applications and recent advancement |
en_US |
dc.type |
Postprint Article |
en_US |