Cooperative P2P Energy Trading in Active Distribution Networks: An MILP-Based Nash Bargaining Solution

This article proposes a cooperative energy market model for an active Distribution Network (DN) by using the theory of Generalized Nash Bargaining (GNB). The proposed energy market has three types of participants: the DN operator, buyers, and sellers. Two energy trading manners are allowed at the sa...

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Bibliographic Details
Published inIEEE transactions on smart grid Vol. 12; no. 2; pp. 1264 - 1276
Main Authors Zhong, Weifeng, Xie, Shengli, Xie, Kan, Yang, Qiyu, Xie, Lihua
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 01.03.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Summary:This article proposes a cooperative energy market model for an active Distribution Network (DN) by using the theory of Generalized Nash Bargaining (GNB). The proposed energy market has three types of participants: the DN operator, buyers, and sellers. Two energy trading manners are allowed at the same time: 1) each of buyers/sellers trades energy with the DN operator; 2) buyers and sellers trade energy in a Peer-to-Peer (P2P) manner and pay network usage fees to the DN operator. In the market, the DN operator actively manages voltage and reactive power (Volt-VAR) via controlling on-load tap changers of transformers and shunt capacitors. The payments among participants are subject to price constraints. The GNB problem for the proposed market is formulated and then decomposed into two subproblems: social welfare maximization problem (P1) and energy trading problem (P2). Both P1 and P2 are nonconvex problems. Next, linearization techniques are employed and a grid propagation algorithm is developed, transforming P1 and P2 into their equivalent Mixed-Integer Linear Programming (MILP) problems. In simulation, the proposed market model is compared with other GNB-based market models. The results show that the proposed one can significantly increase social welfare through Volt-VAR control and also can maximize the extent of fairness of profit allocation under the price constraints.
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ISSN:1949-3053
1949-3061
DOI:10.1109/TSG.2020.3031013