Distributed Day-Ahead Peer-to-Peer Trading for Multi-Microgrid Systems in Active Distribution Networks

Developing a reasonable, efficient distributed market transaction mechanism is an important issue in distribution systems. The gaming relation between distributed transaction market entities has yet to be fully elucidated in various trading links, and the impact of distributed transactions on distri...

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Main Authors: Hong Liu, Jifeng Li, Shaoyun Ge, Xingtang He, Furong Li, Chenghong Gu
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9049140/
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spelling doaj-04b3b24c7f7a4a5fbc0ef395dbdc342a2021-03-30T03:16:42ZengIEEEIEEE Access2169-35362020-01-018669616697610.1109/ACCESS.2020.29836459049140Distributed Day-Ahead Peer-to-Peer Trading for Multi-Microgrid Systems in Active Distribution NetworksHong Liu0https://orcid.org/0000-0002-0175-3667Jifeng Li1https://orcid.org/0000-0001-7895-5753Shaoyun Ge2Xingtang He3Furong Li4Chenghong Gu5Key Laboratory of the Ministry of Education on Smart Power Grids, Tianjin University, Tianjin, ChinaKey Laboratory of the Ministry of Education on Smart Power Grids, Tianjin University, Tianjin, ChinaKey Laboratory of the Ministry of Education on Smart Power Grids, Tianjin University, Tianjin, ChinaKey Laboratory of the Ministry of Education on Smart Power Grids, Tianjin University, Tianjin, ChinaDepartment of Electronic and Electrical Engineering, University of Bath, Bath, U.K.Department of Electronic and Electrical Engineering, University of Bath, Bath, U.K.Developing a reasonable, efficient distributed market transaction mechanism is an important issue in distribution systems. The gaming relation between distributed transaction market entities has yet to be fully elucidated in various trading links, and the impact of distributed transactions on distribution network operations has yet to be comprehensively analyzed. This paper proposes a novel distributed Peer-to-Peer (P2P) day-ahead trading method under multi-microgrid congestion management in active distribution networks. First, a flexible load model for price-based demand response load and an autonomous microgrid economic scheduling model are constructed. Second, under normal operation of the distribution network, a non-cooperative game model and Stackelberg game model are employed to separately and comprehensively analyze gaming relationship among sellers, and between sellers and buyers. Thereafter, a congestion management method based on market capacity is established from the perspective of distribution network control centers. Finally, the impact of end energy consumption characteristics on microgrid economic scheduling and P2P trading is analyzed through a modified IEEE 33-node power distribution system. The economic and technical benefits such as congestion mitigation and network loss reduction that produced by P2P trading to the operation of microgrid systems are analysed with specific indicators.https://ieeexplore.ieee.org/document/9049140/Multi-microgrid clusteractive distribution networkpeer-to-peer tradingnon-cooperative gameStackelberg gamecongestion management
collection DOAJ
language English
format Article
sources DOAJ
author Hong Liu
Jifeng Li
Shaoyun Ge
Xingtang He
Furong Li
Chenghong Gu
spellingShingle Hong Liu
Jifeng Li
Shaoyun Ge
Xingtang He
Furong Li
Chenghong Gu
Distributed Day-Ahead Peer-to-Peer Trading for Multi-Microgrid Systems in Active Distribution Networks
IEEE Access
Multi-microgrid cluster
active distribution network
peer-to-peer trading
non-cooperative game
Stackelberg game
congestion management
author_facet Hong Liu
Jifeng Li
Shaoyun Ge
Xingtang He
Furong Li
Chenghong Gu
author_sort Hong Liu
title Distributed Day-Ahead Peer-to-Peer Trading for Multi-Microgrid Systems in Active Distribution Networks
title_short Distributed Day-Ahead Peer-to-Peer Trading for Multi-Microgrid Systems in Active Distribution Networks
title_full Distributed Day-Ahead Peer-to-Peer Trading for Multi-Microgrid Systems in Active Distribution Networks
title_fullStr Distributed Day-Ahead Peer-to-Peer Trading for Multi-Microgrid Systems in Active Distribution Networks
title_full_unstemmed Distributed Day-Ahead Peer-to-Peer Trading for Multi-Microgrid Systems in Active Distribution Networks
title_sort distributed day-ahead peer-to-peer trading for multi-microgrid systems in active distribution networks
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description Developing a reasonable, efficient distributed market transaction mechanism is an important issue in distribution systems. The gaming relation between distributed transaction market entities has yet to be fully elucidated in various trading links, and the impact of distributed transactions on distribution network operations has yet to be comprehensively analyzed. This paper proposes a novel distributed Peer-to-Peer (P2P) day-ahead trading method under multi-microgrid congestion management in active distribution networks. First, a flexible load model for price-based demand response load and an autonomous microgrid economic scheduling model are constructed. Second, under normal operation of the distribution network, a non-cooperative game model and Stackelberg game model are employed to separately and comprehensively analyze gaming relationship among sellers, and between sellers and buyers. Thereafter, a congestion management method based on market capacity is established from the perspective of distribution network control centers. Finally, the impact of end energy consumption characteristics on microgrid economic scheduling and P2P trading is analyzed through a modified IEEE 33-node power distribution system. The economic and technical benefits such as congestion mitigation and network loss reduction that produced by P2P trading to the operation of microgrid systems are analysed with specific indicators.
topic Multi-microgrid cluster
active distribution network
peer-to-peer trading
non-cooperative game
Stackelberg game
congestion management
url https://ieeexplore.ieee.org/document/9049140/
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