| 引用本文: | 杨朝铭,杨欢红,周徐达,等.基于电碳负荷准线的电动汽车需求响应优化方法研究[J].电力系统保护与控制,2026,54(01):60-70.[点击复制] |
| YANG Chaoming,YANG Huanhong,ZHOU Xuda,et al.Research on optimization methods for electric vehicle demand response based on electricity-carbon customer directrix load[J].Power System Protection and Control,2026,54(01):60-70[点击复制] |
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| 摘要: |
| 电动汽车在实施需求响应、调节电力负荷方面具有巨大潜力。但现有方法主要依赖价格调控和负荷基线，响应目标单一，未充分考虑用户个性化需求及系统不确定性，难以实现理想的用户激励效果。为此，提出基于电碳负荷准线的电动汽车需求响应优化方法。首先，考虑不同节点的停车需求差异及用户充电随机性，并引入动态碳排放因子，构建电动汽车节点电碳耦合需求响应模型。其次，提出负荷准线双目标博弈滚动优化框架，构建负荷准线日前日内滚动优化模型，并通过配电网与电动汽车用户间的双目标主从博弈，精确测算响应结果以设定合理的负荷准线。然后，提出联合博弈优化算法，在降低计算复杂度与缩短迭代时间的同时，确保全局最优解及总体求解效果。算例分析表明，该方法在优化配电网电碳平衡的同时，有效降低了用户响应难度，确保响应后结果符合双方利益，为精准负荷准线设定提供参考。 |
| 关键词: 电动汽车需求响应 电碳耦合 节点负荷准线 联合博弈滚动优化 |
| DOI：10.19783/j.cnki.pspc.250238 |
| 投稿时间：2025-03-07修订日期：2025-05-03 |
| 基金项目:国家自然科学基金项目资助(52177100) |
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| Research on optimization methods for electric vehicle demand response based on electricity-carbon customer directrix load |
| YANG Chaoming1,YANG Huanhong1,ZHOU Xuda2,LI Jun1,ZHANG Weichuan3,WANG Lixiang3 |
| (1.?School of Electric Power Engineering, Shanghai University of Electric Power, Shanghai 200090, China;
2. State Grid Shanghai Direct Current Company, Shanghai 200235, China; 3. Henan Xuji
Instrument Co., Ltd., Xuchang 461000, China) |
| Abstract: |
| Electric vehicles (EVs) have great potential for implementing demand response and regulating power loads. However, existing methods mainly rely on price control and load baselines, with single response objectives, and do not fully consider user-specific needs and system uncertainties, making it difficult to achieve desired user incentives. To address this, an EV demand response optimization method based on electricity-carbon load baselines is proposed. First, an EV node electricity-carbon coupling demand response model is developed, considering parking demand variations, charging randomness, and dynamic carbon emission factors. Then, a customer directrix load dual-objective game rolling optimization framework is introduced, incorporating a day-ahead and intra-day rolling optimization model and a dual-objective leader-follower game between the distribution network and EV users to set more precise customer directrix load. A joint game optimization algorithm is proposed to reduce computational complexity and iteration time while ensuring global optimality and overall solution effectiveness. Case studies show that the method optimizes electricity-carbon balance in the distribution network, effectively reduces EV user response difficulty, ensures mutual benefits, and provide a reference for accurate baseline setting. |
| Key words: electric vehicles demand response electricity-carbon coupling node customer directrix load joint game rolling optimization |
