考虑温度影响的电动汽车集群市场化双型需求响应运营策略

李咸善; 李家辉; 李丹宁; 仇成龙; 张远航; 刘颂凯; 李飞

引用本文:	李咸善,李家辉,李丹宁,等.考虑温度影响的电动汽车集群市场化双型需求响应运营策略[J].电力系统保护与控制,2026,54(09):137-150.
	LI Xianshan,LI Jiahui,LI Danning,et al.Market-oriented dual-type demand response operation strategy for electric vehicle aggregators considering temperature effects[J].Power System Protection and Control,2026,54(09):137-150

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考虑温度影响的电动汽车集群市场化双型需求响应运营策略
李咸善^1,2，李家辉^1,2，李丹宁^1,2，仇成龙^1,2，张远航^1,2，刘颂凯¹，李飞^1,3
1. 梯级水电站运行与控制湖北省重点实验室 (三峡大学)，湖北宜昌 443002；2. 三峡大学电气与新能源学院，湖北宜昌 443002；3. 水资源工程与调度全国重点实验室 (武汉大学)，湖北武汉 430072

摘要:

为应对极端温度对电网灵活性及电动汽车(electric vehicle, EV)运营产生的重大影响，保障电网供电可靠性与多主体运营经济性，提出了一种考虑温度影响的电动汽车聚合商(electric vehicle aggregator, EVA)参与价格引导型和补贴激励型的双型需求响应市场化运营策略。首先，构建了考虑温度影响的EV负荷模型、以及计及温度影响及用户响应意愿的EVA可调度容量评估模型。其次，针对EVA参与日前-日内两阶段双型需求响应市场运营，构建了电力市场运营商(power market operator, PMO)与EVA之间的主从博弈需求响应决策模型。其中，上层为市场出清模型，反映市场供需变化，以市场用能成本最低为目标，决策市场出清电价，引导需求侧参与价格引导型需求响应；下层为EVA双型需求响应决策模型，EVA响应双型需求响应价格，以EVA运营效益最大化为目标，决策其双型需求响应策略。最后，通过算例分析验证了所提策略能够使EVA在不同温度下有效调整竞标策略以实现收益最大化，进而提升电网应对极端温度变化的调度能力。

关键词: 电动汽车温度影响因素电力市场需求响应运营策略

DOI：10.19783/j.cnki.pspc.250937

分类号:

基金项目:国家自然科学基金项目资助(52407118)；水资源工程与调度全国重点实验室开放基金项目资助(2023SDG02)

Market-oriented dual-type demand response operation strategy for electric vehicle aggregators considering temperature effects

LI Xianshan^1,2, LI Jiahui^1,2, LI Danning^1,2, QIU Chenglong^1,2, ZHANG Yuanhang^1,2, LIU Songkai¹, LI Fei^1,3

1. Hubei Provincial Key Laboratory of Operation and Control of Cascade Hydropower Stations (China Three Gorges University), Yichang 443002, China; 2. School of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China; 3. State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072, China

Abstract:

To address the significant impact of extreme temperatures on power system flexibility and electric vehicle (EV) operation, and to ensure both power supply reliability and economic efficiency for multiple stakeholders, a market-oriented dual-type demand response operation strategy for EV aggregators (EVA) is proposed, incorporating temperature effects. The strategy enables participation in both price-based and incentive-based demand response programs. First, an EV load model considering temperature effects is developed, along with an EVA dispatchable capacity evaluation model. Second, a leader-follower game-based decision-making model between the power market operator (PMO) and the EVA is developed. Finally, case study results show that the proposed strategy enables EVA to effectively adjust bidding strategies under varying temperature conditions, thereby maximizing profits and enhancing the power system's dispatching ability.

Key words: electric vehicle temperature effects electricity market demand response operation strategy

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