A Comprehensive Energy System P2P Trading Strategy Based on Blockchain Technology with Multiple Time Scales and Subject Reputation Ratings

Jun Qi, Keke Ding, Lin Qiao, Zhen Luo, Junyou Yang, Haixin Wang, Biqi Liu, Yubo Liu

Abstract

Although Existing research has reduced system uncertainty to some extent through prediction‐based integrated energy output optimization, but has still failed to completely eliminate risks caused by prosumer default behaviors and prediction errors. Therefore, this paper has proposed an integrated peer to peer energy trading strategy based on blockchain technology, multi‐timescale coordination and entity reputation, aiming to significantly reduce system volatility caused by prosumer output uncertainty in regional integrated energy systems. First, this paper has elaborated the operation mode of integrated energy systems and has established a mathematical model for regional integrated energy system clusters. Then, to address default behaviors in energy trading, a contract fulfillment rate‐based reputation evaluation model for systems has been proposed. Furthermore, a multi‐timescale risk management strategy has been developed: in the day‐ahead multi‐energy market, risk‐averse approaches have been adopted to determine optimal trading strategies; in the intraday multi‐energy market, dynamic adjustments have been made based on day‐ahead market decisions; while in the real‐time multi‐energy market, specific trading arrangements among systems have been further refined. Finally, simulation analysis of smart contracts has been conducted on MATLAB and IDE‐Remix platforms, and case study results have demonstrated the rationality and effectiveness of the proposed integrated energy trading mechanism. © 2026 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Source: semanticscholar

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