Nash Equilibrium Estimation and Analysis in Joint Peer-to-Peer Electricity and Carbon Emission Auction Market With Microgrid Prosumers

被引:10
作者
Zhu, Ziqing [1 ]
Chan, Ka Wing [1 ]
Bu, Siqi [1 ]
Zhou, Bin [2 ]
Xia, Shiwei [3 ]
机构
[1] Hong Kong Polytech Univ, Dept Elect Engn, Hong Kong, Peoples R China
[2] Hunan Univ, Coll Elect & Informat Engn, Changsha 410012, Hunan, Peoples R China
[3] North China Elect Power Univ, Elect Engn, Beijing 102206, Peoples R China
关键词
Uncertainty; Peer-to-peer computing; Electricity supply industry; Carbon dioxide; Risk management; Nash equilibrium; Microgrids; Bidding strategy; conditional value-at-risk; microgrid; multi-agent reinforcement learning; P2P energy trading; PRICE; LEVEL;
D O I
10.1109/TPWRS.2022.3225575
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The joint Peer-to-Peer (P2P) electricity market (EM) and carbon emission auction market (CEAM) among prosumer microgrids (MGs) in the distribution network is a promising paradigm to facilitate the participation of distributed energy resources (DERs) and incentivize the decarbonization. In this market, MGs will modify their bidding strategies to be adaptive to other rival MGs' for profit maximization. Such modification will converge to the Nash Equilibrium Point (NEP), where each MG cannot obtain more profits by modifying its strategy subject to the fixed strategy of other rival MGs. In this paper, the NEP under such a joint market paradigm is investigated, in which MGs will trade electricity in the EM and purchase carbon emission quotas (CEQs) in the CEAM. In addition, MGs must adjust their bidding strategies considering penalties due to deviations between day-ahead (DA) scheduling and real-time (RT) procurement caused by uncertainties of net load, as well as the price fluctuation in the CEAM. The NEP is estimated by a novel Multi-agent Deep Deterministic Policy Gradient (MADDPG) algorithm, and the risk mitigation is achieved by incorporating the conditional value-at-risk (CVaR) constraint. The computational performance and effectiveness of risk mitigation of this proposed algorithm, and the obtained NEP in the joint EM and CEAM, are analyzed in the case studies.
引用
收藏
页码:5768 / 5780
页数:13
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