AI 中文总结
本文针对同一聚合器协调的非合作换电站，构建分层博弈论模型证明子博弈完美纳什均衡的存在与唯一性，提出最优定价充电策略及需求波动处理方法，仿真显示可提升换电站利润至少18.1%并实现电网削峰填谷。
AI 中文摘要
换电是电动汽车（EV）快速补能的方式。随着越来越多主体参与建设换电站（BSS），非合作换电站如何在竞争市场中最大化自身利润需要进一步研究。本文聚焦同一聚合器协调竞争换电站的实际场景，为研究最优定价与电池充电，构建了分层博弈论模型：第一阶段换电站在日前市场确定换电价格，第二阶段在实时市场确定最优电池充电策略。本文严格证明了子博弈完美纳什均衡（SPNE）的存在性与唯一性，该唯一性为均衡策略在竞争环境中的最优性提供了理论支撑。基于唯一的SPNE，本文为每个换电站提出了竞争市场中最大化利润的最优定价与充电策略，还提出了应对换电需求意外波动的预测误差处理方法。本文基于中国西安的真实数据开展了12个换电站系统的仿真，结果显示所提定价与充电策略可使单个换电站利润至少提升18.1%，且最优充电策略自然实现了电网的削峰填谷。
英文摘要
Battery swapping is a rapid way to recharge electric vehicles (EVs). As more and more entities are involved in building Battery Swapping Stations (BSSs), how non-cooperative BSSs maximize their profit in a competitive market needs further investigation. In this paper, we focus on a practical scenario where competitive BSSs are coordinated by the same aggregator. To study the optimal pricing and battery charging, we formulate a hierarchical game-theoretic model, where BSSs determine the swapping price in the day-ahead market in the first stage, and then determine the optimal battery charging strategy in the real-time market in the second stage. We rigorously prove the existence and uniqueness of the Subgame Perfect Nash Equilibrium (SPNE). In particular, the uniqueness property provides theoretical support that the strategy under equilibrium is optimal in the competitive environment. Based on the unique SPNE, we propose an optimal pricing and charging strategy for each BSS to maximize profit in the competitive market. A prediction error handling method is also proposed to deal with unexpected fluctuations in swapping demand. Our simulation with a 12-BSS system based on real-life data from Xi'an, China shows that our pricing and charging strategy increases the individual BSS profit by at least 18.1\%, while the optimal charging strategy naturally achieves peak shaving for the power grid.
CommentsPublished in IEEE Transactions on Mobile Computing, vol. 23, no. 12, pp. 13573-13588, Dec. 2024
Journal refIEEE Trans. Mobile Comput. 23(12), 13573-13588 (2024)
