PDF(2772 KB)
An Optimization Strategy for Distributed Energy Trading Based on Improved Iterative Auction Method
LIU Xiaojun, WANG Gang
Distributed Energy ›› 2025, Vol. 10 ›› Issue (4) : 35-43.
PDF(2772 KB)
PDF(2772 KB)
An Optimization Strategy for Distributed Energy Trading Based on Improved Iterative Auction Method
In the context of the increasing penetration of distributed generation, peer-to-peer (P2P) trading is one of the effective ways to improve energy utilization. However, during the trading process, improper behavior of contracted users and power losses in network transmission can lead to transaction failures and higher transmission costs. Accordingly, this paper proposes a distributed reputation- and distance-driven iterative auction mechanism aimed at facilitating energy trading between users with good reputations and those with similar power demands. By combining historical trading performance and the power distance between users, a reputation-distance index is constructed and integrated into the auction matching process. Subsequently, a game-theory-based adaptive algorithm is employed to model the iterative auction and achieve Nash equilibrium. Case studies demonstrate that the proposed decentralized mechanism effectively reduces network losses and peak loads, enhances power reliability, and improves economic efficiency and social welfare. Specifically, compared to traditional models that do not consider reputation or distance, the proposed mechanism reduces network losses by 54%, increases the market share of high-reputation users by 7.95%, improves economic efficiency by 10%, and boosts social welfare by 13.58%.
mechanism design / peer-to-peer (P2P) energy trading / iterative auction / trading strategy
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