Performance Evaluation of Peer-to-Peer Energy Sharing Models. (December 2017)

• Record Type: Journal Article
• Authors: Zhou, Yue; Wu, Jianzhong; Long, Chao; Cheng, Meng; Zhang, Chenghua
• Is Part Of: Energy procedia. Volume 143(2017)
• Page Start: 817
• Page End: 822
• Publication Date: 2017-12
• Subjects: Energy sharing -- Peer to peer -- Prosumers -- Performance evaluation -- Agent-based modelling -- Reinforcement learning; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2017.12.768
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: With the increasing installation of distributed generation at the demand side, an increasing number of consumers become prosumers, and many peer-to-peer (P2P) energy sharing models have been proposed to reduce the energy bill of the prosumers through stimulating energy sharing and demand response. In this paper, a three-stage evaluation methodology is proposed to assess the economic performance of P2P energy sharing models. First of all, joint and individual optimization are established to identify the value contained in the energy sharing region. The overall energy bill of the prosumer population is then estimated through an agent-based modelling with reinforcement learning for each prosumer. Finally, a performance index is defined to quantify the economic performance of P2P energy sharing models. Simulation results verify the effectiveness of the proposed evaluation methodology, and compare three existing P2P energy sharing models in a variety of electricity pricing environments.