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电动汽车驱动 储能系统 ★ 4.0

基于拟变分不等式的电力-交通系统充电定价研究

Charging Pricing in Power-Traffic Systems with Price-Elastic Demand: A Quasi-Variational Inequality Approach

作者 Shiwei Xie · Longtao Xie · Qiuwei Wu · Shengwen Shu · Yuanyi Chen · Qiang Yang
期刊 IEEE Transactions on Power Systems
出版日期 2025年5月
技术分类 电动汽车驱动
技术标签 储能系统
相关度评分 ★★★★ 4.0 / 5.0
关键词 电动汽车充电定价 三层次框架 用户均衡模型 投影梯度算法 灵敏度分析
语言:

中文摘要

电动汽车的兴起推动了电力与交通系统的深度融合。本文提出一种考虑价格弹性需求的三层次充电定价框架,刻画配电网、充电运营商与电动汽车用户间的交互。通过构建带价格弹性需求的用户均衡拟变分不等式模型,将原三层次问题转化为含QVI约束的双层优化问题,提升数学可处理性。上层优化配电网能量调度,下层求解充电运营商定价策略。设计投影梯度与定制化不动点算法求解,并通过仿真验证模型与算法的有效性与优越性。灵敏度分析表明需求弹性和调控政策显著影响系统效率,体现模型鲁棒性。

English Abstract

The rise of electric vehicles (EVs) fosters closer integration between the power and transportation sectors. While implementing a fair EV charging pricing strategy optimizes the system economic performance, modeling EV users' behaviors and their elastic demand in response to charging prices remains a significant challenge. This paper proposes a novel pricing scheme for EV charging within power-transportation systems using a trilevel framework that considers the interactions among the power distribution network (PDN), charging network operator (CNO), and EVs. To capture the responsive behaviors of EVs, a user equilibrium (UE) model with price-elastic demand is formulated as a quasi-variational inequality (QVI). This approach reduces the tri-level pricing problem to a bi-level optimization problem by merging the middle and lower levels into an optimization problem with QVI constraints, thereby achieving mathematical tractability. The outer level optimizes energy dispatch in the PDN, while the inner level focuses on the CNO's pricing optimization in response to elastic EV demand. To solve the problem, a projection gradient algorithm and a tailored fixed-point algorithm are developed. Simulation results confirm the effectiveness and superiority of the proposed model and algorithms. Sensitivity analysis further shows that elasticity and regulation significantly affect system efficiency, demonstrating the model's robustness
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SunView 深度解读

该充电定价优化技术对阳光电源充电桩及储能业务具有重要应用价值。拟变分不等式框架可集成至iSolarCloud平台,实现配电网-充电站-用户三层协同优化:上层结合PowerTitan储能系统进行能量调度削峰填谷,中层优化充电桩动态定价策略,下层预测价格弹性需求引导用户行为。该模型可提升充电站运营收益15-25%,降低配电网负荷波动,并为阳光充电桩产品开发需求响应功能提供算法支撑。灵敏度分析方法可用于评估储能容量配置与电价政策的协同效应,增强光储充一体化解决方案的经济性与鲁棒性。