Rank‐based energy scheduling strategy of networked microgrids in distribution systems

Abstract Microgrids (MGs) have emerged as a key platform for integrating distributed energy resources into distribution systems. However, a high penetration of renewable energy resources in an MG causes an imbalance frequently between energy generation and load. One solution to this problem is inter...

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Autores principales:	Nitesh Funde, Sung‐Guk Yoon
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2022
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/00e0718f427d43ed8e5f200106595bba
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spelling	oai:doaj.org-article:00e0718f427d43ed8e5f200106595bba2021-12-02T14:01:23ZRank‐based energy scheduling strategy of networked microgrids in distribution systems1751-86951751-868710.1049/gtd2.12279https://doaj.org/article/00e0718f427d43ed8e5f200106595bba2022-01-01T00:00:00Zhttps://doi.org/10.1049/gtd2.12279https://doaj.org/toc/1751-8687https://doaj.org/toc/1751-8695Abstract Microgrids (MGs) have emerged as a key platform for integrating distributed energy resources into distribution systems. However, a high penetration of renewable energy resources in an MG causes an imbalance frequently between energy generation and load. One solution to this problem is internal energy trading among MGs, where MGs trade (i.e. buy or sell) energy with other MGs in the network. In internal trading, multiple buyer MGs may compete to obtain energy from seller MGs with surplus energy. By contrast, seller MGs also compete to sell their surplus to those confronted with a deficit. Considering this scenario, we propose a novel rank‐based energy scheduling strategy for networked MGs in a distribution system to solve the competition between buyer and seller MGs. The technique for order of preference by similarity to the ideal solution method, which is a multi‐criteria decision‐making approach, is applied to prioritise the MGs. The proposed strategy determines the amount of internal energy to trade for each seller/buyer MG. Different from existing mechanisms, the proposed rank‐based approach evaluates each MG with respect to four criteria: ratio of energy, forecasting accuracy, contribution of supply, and historical performance. The proposed strategy is compared with existing no‐rank‐based scheduling and absolute contribution‐based method. Moreover, the effect of each criterion on the cost of each MG is illustrated by considering and disregarding the criterion in the proposed strategy that demonstrates the effectiveness of the proposed strategy in reducing the cost of MGs according to their rank in the network.Nitesh FundeSung‐Guk YoonWileyarticleDistribution or transmission of electric powerTK3001-3521Production of electric energy or power. Powerplants. Central stationsTK1001-1841ENIET Generation, Transmission & Distribution, Vol 16, Iss 1, Pp 84-98 (2022)
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 Nitesh Funde Sung‐Guk Yoon Rank‐based energy scheduling strategy of networked microgrids in distribution systems
description	Abstract Microgrids (MGs) have emerged as a key platform for integrating distributed energy resources into distribution systems. However, a high penetration of renewable energy resources in an MG causes an imbalance frequently between energy generation and load. One solution to this problem is internal energy trading among MGs, where MGs trade (i.e. buy or sell) energy with other MGs in the network. In internal trading, multiple buyer MGs may compete to obtain energy from seller MGs with surplus energy. By contrast, seller MGs also compete to sell their surplus to those confronted with a deficit. Considering this scenario, we propose a novel rank‐based energy scheduling strategy for networked MGs in a distribution system to solve the competition between buyer and seller MGs. The technique for order of preference by similarity to the ideal solution method, which is a multi‐criteria decision‐making approach, is applied to prioritise the MGs. The proposed strategy determines the amount of internal energy to trade for each seller/buyer MG. Different from existing mechanisms, the proposed rank‐based approach evaluates each MG with respect to four criteria: ratio of energy, forecasting accuracy, contribution of supply, and historical performance. The proposed strategy is compared with existing no‐rank‐based scheduling and absolute contribution‐based method. Moreover, the effect of each criterion on the cost of each MG is illustrated by considering and disregarding the criterion in the proposed strategy that demonstrates the effectiveness of the proposed strategy in reducing the cost of MGs according to their rank in the network.
format	article
author	Nitesh Funde Sung‐Guk Yoon
author_facet	Nitesh Funde Sung‐Guk Yoon
author_sort	Nitesh Funde
title	Rank‐based energy scheduling strategy of networked microgrids in distribution systems
title_short	Rank‐based energy scheduling strategy of networked microgrids in distribution systems
title_full	Rank‐based energy scheduling strategy of networked microgrids in distribution systems
title_fullStr	Rank‐based energy scheduling strategy of networked microgrids in distribution systems
title_full_unstemmed	Rank‐based energy scheduling strategy of networked microgrids in distribution systems
title_sort	rank‐based energy scheduling strategy of networked microgrids in distribution systems
publisher	Wiley
publishDate	2022
url	https://doaj.org/article/00e0718f427d43ed8e5f200106595bba
work_keys_str_mv	AT niteshfunde rankbasedenergyschedulingstrategyofnetworkedmicrogridsindistributionsystems AT sunggukyoon rankbasedenergyschedulingstrategyofnetworkedmicrogridsindistributionsystems
_version_	1718392119905746944

Rank‐based energy scheduling strategy of networked microgrids in distribution systems

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