计及运营特性的电动汽车换电站时空双层调度  

Study on Electric Vehicle Battery Swapping Station Space-Time Double Scheduling Consider in it's Operating Characteristics

作　　者：张颖[1] 容展鹏 张宇雄[1] 扈海泽 赵军[1] 付超[1] 

机构地区：[1]长沙理工大学电气与信息工程学院,湖南省长沙市410004

出　　处：《电网技术》2016年第9期2616-2622,共7页Power System Technology

摘　　要：为实现电力系统与电动汽车换电站运营系统的有机融合,在进行电网调度最优化的同时兼顾保障换电站运营,提出了将电动汽车换电站运营参数构建惩罚函数加入调度目标函数的模型。该模型采用双层时空解耦结构,上层模型以整体代理的方式实现换电站在时间尺度的多目标优化调度(包括负荷波动、峰谷差最小),下层模型在空间尺度上合理分配各换电站充电计划来调节包含间歇性分布式电源的电网潮流分布,实现网损最小化,同时引入运营惩罚函数实现换电站运营状况对电网的反馈。之后,采用自适应变异粒子群算法对提出的双层系统进行迭代求解。最后在修改的IEEE 30节点算例中说明该调度模型的作用。To realize organic integration of power system with EVBSS operation system, this paper provides a model putting EVBSS operating parameters, including penalty parameter, into dispatching objective function. So that EVBSS can work smoothly while power grid dispatching is optimized. The model adopts double space-time decoupling structure. The upper model achieves the goal of EVBSS multi-objective dispatching optimization （including minimization of loading fluctuation and peak-valley difference） in time scale by entire agent. To minimize network loss, the lower model distributes equitably every station charging plan in spatial scales to adjust power grid flow distribution, containing intermittent characteristic of distributed generation. Operating penalty parameter is introduced to realize feedback to power grid from EVBSS. Then adaptive mutation particle swarm optimization （AMPSO） algorithm is used to solve iteratively the double system, and illustrates role of scheduling model with modified IEEE30 node example.

关 键 词：电动汽车换电站 运营特性 双层调度 粒子群算法 

分 类 号：TM76[电气工程—电力系统及自动化]