A novel adaptive penalty mechanism for Peer-to-Peer energy trading

Bidan Zhang, Yang Du, Xiaoyang Chen, Eng Gee Lim, Lin Jiang and Ke Yan

Applied Energy, 2022, vol. 327, issue C, No S0306261922013824

Abstract: With the rapid development of Distributed Energy Sources (DERs), Peer-to-Peer (P2P) energy trading is regarded as an effective scheme to improve local energy utilization. Nevertheless, unlike wholesale electricity markets of the current grid size, small-scale prosumers and highly unpredictable intermittent DERs account for a significant proportion of P2P markets, leading to an escalation of market uncertainties. To facilitate effective market functionality, penalty mechanisms for unqualified participants are essential, as is typically the case in the wholesale electricity market. However, there has been little discussion of the use of penalty mechanisms in P2P markets. In this context, we propose a novel adaptive penalty mechanism (APM) to drive the defaulting prosumers to fulfill orders. Unlike the traditional two-dimensional (price, quantity) penalty price, APM uses a three-dimensional penalty and introduces deviation percentage factors to reduce the risk of excessive penalty rates. Penalty prices are determined by utilizing the distributed default clearing algorithm to adapt to market conditions, thereby preventing deviations in clearing prices. Case studies are conducted to demonstrate the feasibility and efficiency of the proposed APM in the P2P market. The results indicate that the APM strike an appropriate between cost-effectiveness and regulation, requiring about 20% less reserve capacity than the severe penalty.

Keywords: Peer-to-Peer energy trading; Penalty mechanism; Double auction; Energy management system; Uncertainty (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (5)

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DOI: 10.1016/j.apenergy.2022.120125

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