计及用户意愿的电动汽车聚合商主从博弈优化调度策略

doi:10.19595/j.cnki.1000-6753.tces.230923

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摘要

规模化电动汽车作为一种新型负荷在参与备用市场、实现负荷削峰填谷方面具备巨大潜力。但由于电动汽车用户参与聚合商调控的意愿存在不确定性,导致电动汽车集群备用容量难以精确量化,影响聚合商参与市场的最优决策。针对用户意愿不确定性以及聚合商与电动汽车用户之间的利益冲突问题,本文提出了计及用户意愿的电动汽车聚合商主从博弈优化调度策略。首先,考虑用户灵活用车时间焦虑成本与电池损耗焦虑成本两个因素,量化电动汽车用户集群参与调控意愿。其次,建立以自身效益最大化为目标的电动汽车聚合商-电动汽车用户主从博弈模型,提出模型转化与高效迭代求解方法。最后,通过算例分析了用户意愿表征方法的有效性,所提博弈模型显著提高了电动汽车聚合商和电动汽车用户的经济性,同时实现了削峰填谷,促进了电网经济安全运行。

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关键词 ：电动汽车, 用户意愿, 主从博弈, 备用市场

Abstract：

As a new type of load, large-scale electric vehicles (EV) have great potential in participating in the reserve market and realizing load shaving and valley filling. However, due to the uncertainty of the user intention to participate in the regulation of electric vehicles aggregators (EVA), it is difficult to accurately quantify the reserve capacity of EV clusters, which affects the optimal decision-making of aggregators to participate in the market. Aiming at the uncertainty of user intention and the conflict of interests between EVA and EV users, this paper proposed an EVA Stackelberg game optimization dispatch strategy considering user intention.
First of all, the anxiety of battery loss and the anxiety of time to flexibly use EV are portrayed respectively through the coefficient of exclusion psychology combined with Exponential function and decision factors combined with EV online time, and the irrational behavior of users in the decision-making process is reflected through the binomial distribution to determine whether a single user is willing to participate in EVA regulation, so as to quantify the intention of EV user clusters to participate in EVA regulation. Secondly, taking into account user intention, an EVA-EV Stackelberg game model is established with the goal of maximizing self-benefits. A probability distribution transformation and feedback loop iteration solution method of the intention model is proposed to achieve rapid convergence of the dual objective game problem, and the optimal reserve compensation price for EVA and the reserve capacity that the EV cluster can provide under its stimulation are obtained. Finally, the effectiveness of the intention representation method and the feasibility of the iterative solution method of the proposed Stackelberg game model are proved through a numerical example. It can be seen that the Stackelberg game model can significantly improve the economy of EVA and EV users, while achieving load peak shaving and valley filling, and promoting the Economic security operation of the grid.
From the perspective of time cost and economic cost, the EV user intention model of the anxiety of battery loss and the anxiety of time to flexibly use EV is described, and the user intention evaluation is carried out based on the binomial distribution, which fully considers the uncertainty in the actual decision-making process of EV users. When the EV cluster reaches a certain size, the intention model is stable and feasible. Based on the above intention model, construct a Stackelberg game with EVA as the main body, achieve price incentives for EV users through cyclic iterative feedback, and optimize EV users' intention to make decisions based on price incentives. Balance the conflict of interest between EVA and EV users through real-time information exchange feedback mechanism, and develop the optimal reserve compensation price for EVA, achieving overall benefit balance between the two. The Stackelberg game model is established on the basis of an optimization model guided by the time-of-use electricity prices, which can achieve effective peak shaving and valley filling effects while achieving economic goals, reduce the peak valley difference of power grid load, and is of great significance for maintaining stable operation of the grid.

Key words： Electric vehicle user intention Stackelberg game reserve market

收稿日期: 2023-06-15

PACS:

TM73

基金资助:

国家自然科学基金资助项目（52177080）

通讯作者: 胡俊杰男,1986年生,教授,博士生导师,研究方向为电动汽车与电网的互动等。E-mail：junjiehu@ncepu.edu.cn

作者简介: 房宇轩男,2000年生,硕士研究生,研究方向为电动汽车优化调度与人工智能等。E-mail：fangyx@ncepu.edu.cn

引用本文:

房宇轩, 胡俊杰, 马文帅. 计及用户意愿的电动汽车聚合商主从博弈优化调度策略[J]. 电工技术学报, 0, (): 230923-. Fang Yuxuan, Hu Junjie, Ma Wenshuai. Optimal Dispatch Strategy for Electric Vehicle Aggregators Based on Stackelberg Game Theory Considering User Intention. Transactions of China Electrotechnical Society, 0, (): 230923-.

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