A multi‐objective optimization for planning of networked microgrid using a game theory for peer‐to‐peer energy trading scheme

Abstract In this paper, a multi‐objective optimization technique is proposed for the planning of a networked microgrid based on peer‐to‐grid (P2G) and peer‐to‐peer (P2P) energy trading schemes. Two different criteria's including annual profit and energy index of reliability are taken into consi...

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Autores principales:	Liaqat Ali, S. M. Muyeen, Hamed Bizhani, Arindam Ghosh
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	Distribution or transmission of electric power TK3001-3521 Production of electric energy or power. Powerplants. Central stations TK1001-1841
Acceso en línea:	https://doaj.org/article/f024519821bc476ca6ae09f33f772c93
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spelling	oai:doaj.org-article:f024519821bc476ca6ae09f33f772c932021-11-16T15:47:59ZA multi‐objective optimization for planning of networked microgrid using a game theory for peer‐to‐peer energy trading scheme1751-86951751-868710.1049/gtd2.12308https://doaj.org/article/f024519821bc476ca6ae09f33f772c932021-12-01T00:00:00Zhttps://doi.org/10.1049/gtd2.12308https://doaj.org/toc/1751-8687https://doaj.org/toc/1751-8695Abstract In this paper, a multi‐objective optimization technique is proposed for the planning of a networked microgrid based on peer‐to‐grid (P2G) and peer‐to‐peer (P2P) energy trading schemes. Two different criteria's including annual profit and energy index of reliability are taken into consideration to form a multi‐objective function. The networked microgrid consists of three individual microgrids containing their own combinations of generation resources, batteries and residential loads. All microgrids are connected together and also to the main grid to meet the energy exchange requirements of P2P energy trading. A cooperative game theory technique based on a particle swarm optimization algorithm is used to model the networked microgrid, and to find the suitable sizes of the players that simultaneously maximize the payoff values of both objective functions. Besides, a comparative analysis is carried out for both P2G and P2P energy trading schemes. The results show that the outcomes are maximum when both criteria are considered in the optimization and P2P energy trading is carried out. The sensitivity analysis is performed on the selected parameters and verified the right change 0.003% and 4.5% in discount rate and electricity prices, respectively.Liaqat AliS. M. MuyeenHamed BizhaniArindam GhoshWileyarticleDistribution or transmission of electric powerTK3001-3521Production of electric energy or power. Powerplants. Central stationsTK1001-1841ENIET Generation, Transmission & Distribution, Vol 15, Iss 24, Pp 3423-3434 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Distribution or transmission of electric power TK3001-3521 Production of electric energy or power. Powerplants. Central stations TK1001-1841
spellingShingle	Distribution or transmission of electric power TK3001-3521 Production of electric energy or power. Powerplants. Central stations TK1001-1841 Liaqat Ali S. M. Muyeen Hamed Bizhani Arindam Ghosh A multi‐objective optimization for planning of networked microgrid using a game theory for peer‐to‐peer energy trading scheme
description	Abstract In this paper, a multi‐objective optimization technique is proposed for the planning of a networked microgrid based on peer‐to‐grid (P2G) and peer‐to‐peer (P2P) energy trading schemes. Two different criteria's including annual profit and energy index of reliability are taken into consideration to form a multi‐objective function. The networked microgrid consists of three individual microgrids containing their own combinations of generation resources, batteries and residential loads. All microgrids are connected together and also to the main grid to meet the energy exchange requirements of P2P energy trading. A cooperative game theory technique based on a particle swarm optimization algorithm is used to model the networked microgrid, and to find the suitable sizes of the players that simultaneously maximize the payoff values of both objective functions. Besides, a comparative analysis is carried out for both P2G and P2P energy trading schemes. The results show that the outcomes are maximum when both criteria are considered in the optimization and P2P energy trading is carried out. The sensitivity analysis is performed on the selected parameters and verified the right change 0.003% and 4.5% in discount rate and electricity prices, respectively.
format	article
author	Liaqat Ali S. M. Muyeen Hamed Bizhani Arindam Ghosh
author_facet	Liaqat Ali S. M. Muyeen Hamed Bizhani Arindam Ghosh
author_sort	Liaqat Ali
title	A multi‐objective optimization for planning of networked microgrid using a game theory for peer‐to‐peer energy trading scheme
title_short	A multi‐objective optimization for planning of networked microgrid using a game theory for peer‐to‐peer energy trading scheme
title_full	A multi‐objective optimization for planning of networked microgrid using a game theory for peer‐to‐peer energy trading scheme
title_fullStr	A multi‐objective optimization for planning of networked microgrid using a game theory for peer‐to‐peer energy trading scheme
title_full_unstemmed	A multi‐objective optimization for planning of networked microgrid using a game theory for peer‐to‐peer energy trading scheme
title_sort	multi‐objective optimization for planning of networked microgrid using a game theory for peer‐to‐peer energy trading scheme
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/f024519821bc476ca6ae09f33f772c93
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A multi‐objective optimization for planning of networked microgrid using a game theory for peer‐to‐peer energy trading scheme

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