考虑路网和用户满意度的集群电动汽车主从博弈优化调度策略OA北大核心CSTPCD
Stackelberg game optimization scheduling strategy for aggregated electric vehicles considering customer satisfaction and the road network
传统的电动汽车(electric vehicle,EV)集中优化方法在实际应用中面临调度困难、计算量大、缺乏真实数据支撑等问题,无法准确揭示各主体间的交互行为.为此,提出一种考虑路网和用户满意度的集群EV主从博弈优化调度策略.首先基于真实出行数据和路网数据模拟用户出行行为.其次,负荷聚合商(load aggregator,LA)整合EV负荷资源,对相似出行特性的EV进行聚类.在双层主从博弈模型中,LA作为上层领导者,聚类后的各EV子群作为下层跟随…查看全部>>
Traditional centralized optimization methods for electric vehicles(EVs)are faced with problems such as scheduling difficulty,a large amount of computation and lack of real data support in practical application,and they cannot accurately reveal the interaction behavior among various entities.Therefore,a Stackelberg game optimization scheduling strategy for aggregated EVs considering user satisfaction and the road network is proposed.First,it simulates user tr…查看全部>>
张美霞;王晓晴;杨秀;张安;付御临
上海电力大学电气工程学院,上海 200090上海电力大学电气工程学院,上海 200090上海电力大学电气工程学院,上海 200090上海电力大学电气工程学院,上海 200090上海电力大学电气工程学院,上海 200090
集群电动汽车主从博弈负荷聚合商需求响应K-means++聚类算法用户满意度
aggregated electric vehicleStackelberg gameload aggregatordemand responseK-means++ clustering algorithmcustomer satisfaction
《电力系统保护与控制》 2024 (3)
电力系统可靠性
1-11,11
This work is supported by the National Natural Science Foundation of China(No.51725701). 国家自然科学基金项目资助(51725701)上海电力人工智能工程技术研究中心项目资助(19DZ2252800)
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