An efficient P2P energy trading platform based on evolutionary games for prosumers in a community

Fernandez, E; Hossain, MJ; Nawazish Ali, SM; Sharma, V

An efficient P2P energy trading platform based on evolutionary games for prosumers in a community

Fernandez, E Hossain, MJ Nawazish Ali, SM Sharma, V

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Publisher:: ELSEVIER
Publication Type:: Journal Article
Citation:: Sustainable Energy, Grids and Networks, 2023, 34
Issue Date:: 2023-06-01

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Field	Value	Language
dc.contributor.author	Fernandez, E
dc.contributor.author	Hossain, MJ
dc.contributor.author	Nawazish Ali, SM
dc.contributor.author	Sharma, V
dc.date.accessioned	2024-02-02T00:22:15Z
dc.date.available	2024-02-02T00:22:15Z
dc.date.issued	2023-06-01
dc.identifier.citation	Sustainable Energy, Grids and Networks, 2023, 34
dc.identifier.issn	2352-4677
dc.identifier.issn	2352-4677
dc.identifier.uri	http://hdl.handle.net/10453/175261
dc.description.abstract	This paper proposes a game-theoretic community energy management model that encourages energy trading between members of a community. The members of the community are classified as consumers and vendors. These roles are interchangeable based on the day-ahead power consumption profile. An evolutionary game is proposed to model the consumer dynamics in selecting the vendor. The vendors can select the consumer to whom they wish to sell the power by setting prices that attract consumers. Therefore, a game exists between the vendors in which competitive prices are set to lure the consumers. The game converges at a Nash equilibrium. The results of the algorithm are the preference of consumers to each vendor and the price of power set by each vendor. The interaction between various entities is modeled by a Stackelberg game. The proposed model is tested in a community in Sydney with renewable energy generators and battery storage systems. Results show the cost savings for the consumers and the profits made by the vendors. The convergence of the models shows the effectiveness of energy trading within the community for financial gains and energy conservation. The proposed model show that profits can be increased and the burden on the grid could be reduced if demand response strategies are adopted and coupled with storage systems.
dc.language	English
dc.publisher	ELSEVIER
dc.relation.ispartof	Sustainable Energy, Grids and Networks
dc.relation.isbasedon	10.1016/j.segan.2023.101074
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.subject	0906 Electrical and Electronic Engineering
dc.subject.classification	4008 Electrical engineering
dc.title	An efficient P2P energy trading platform based on evolutionary games for prosumers in a community
dc.type	Journal Article
utslib.citation.volume	34
utslib.for	0906 Electrical and Electronic Engineering
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	embargoed	*
utslib.copyright.embargo	2025-06-01T00:00:00+1000Z
dc.date.updated	2024-02-02T00:22:14Z
pubs.publication-status	Published
pubs.volume	34

Abstract:

This paper proposes a game-theoretic community energy management model that encourages energy trading between members of a community. The members of the community are classified as consumers and vendors. These roles are interchangeable based on the day-ahead power consumption profile. An evolutionary game is proposed to model the consumer dynamics in selecting the vendor. The vendors can select the consumer to whom they wish to sell the power by setting prices that attract consumers. Therefore, a game exists between the vendors in which competitive prices are set to lure the consumers. The game converges at a Nash equilibrium. The results of the algorithm are the preference of consumers to each vendor and the price of power set by each vendor. The interaction between various entities is modeled by a Stackelberg game. The proposed model is tested in a community in Sydney with renewable energy generators and battery storage systems. Results show the cost savings for the consumers and the profits made by the vendors. The convergence of the models shows the effectiveness of energy trading within the community for financial gains and energy conservation. The proposed model show that profits can be increased and the burden on the grid could be reduced if demand response strategies are adopted and coupled with storage systems.

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http://hdl.handle.net/10453/175261