Incentivizing distributed energy trading among prosumers: A general Nash bargaining approach. (October 2021)

• Record Type: Journal Article
• Authors: Li, Guanguan; Li, Qiqiang; Song, Wen; Wang, Luhao
• Is Part Of: International journal of electrical power & energy systems. Volume 131(2021)
• Publication Date: 2021-10
• Subjects: Distributed energy trading -- General Nash bargaining -- Bargaining power -- Benefits allocation -- Distributed ADMM; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2021.107100
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: Solved a distributed energy trading problem among prosumers without energy markets. Developed an incentive scheme considering the benefits for sharing idle resources. Designed a GNB based framework to depict energy trading and allocate benefits. Quantified prosumers' contribution and ensured fairness of benefits allocation. Realized parallel computing for energy trading problem and safeguarded privacy. Abstract: In this paper, we study the energy interaction problem among the autonomous prosumers, and develop an incentive scheme to encourage proactive energy trading. Specifically, without the need for any coordinators, each prosumer makes optimal strategy to share idle resources (renewable energy or loads) and maximizes the social welfare of a multi prosumers system. To incentivize proactive energy trading among prosumers, an incentive scheme is designed to achieve the fair benefits allocation according to their contributions. According to the summation of daily net transaction power, we quantify prosumers' contributions by leveraging the bargaining power combined with the rate of return. Based on various bargaining power, a distributed energy trading problem is formulated as a general Nash bargaining problem. We propose a distributed solution method with disclosing limited information to preserve prosumers' privacy. Simulations on different cases are conducted based on the actual data in Shanghai, China. Through a practical case study, the effectiveness of the method is verified in terms of distributed energy trading and fair benefits allocation.