考虑电动汽车负荷的微电网容量优化配置  

Optimized Configuration of Microgrid Capacity Considering Electric Vehicle Load

作　　者：陈腾生 李箭 郭红霞[2] 徐嘉启 Chen Tengsheng;Li Jian;Guo Hongxia;Xu Jiaqi(Guangdong Shunde Electric Power Design Institute Co.,Ltd.,Foshan Guangdong 528399,China;School of Electric Power,South China University of Technology,Guangzhou Guangdong 510641,China)

机构地区：[1]广东顺德电力设计院有限公司,广东佛山528399 [2]华南理工大学电力学院,广东广州510641

出　　处：《电气自动化》2024年第4期5-10,共6页Electrical Automation

基　　金：广东省自然科学基金面上项目(2021A1515012073);广东汇源通集团有限公司科技项目“考虑需求响应的电动汽车充电站优化运行”(GS20220108)。

摘　　要：随着“双碳”目标的推进和分布式新能源的快速发展,电网面临着巨大的挑战。为了平衡电动汽车的波动性和新能源出力的随机性,缓解弃风弃光和大规模电动汽车入网对电网造成的冲击,采用蒙特卡洛法模拟电动汽车入网数据,同时结合电动汽车负荷转移策略对微电网进行优化配置,建立以年等值收益为优化目标的微电网优化配置模型,并评估配置结果。通过采用场景缩减法和改进粒子群算法求解模型。算例结果证明了优化配置模型的合理性和经济性。With the promotion of the goals of"Carbon Peaking and Carbon Neutrality"and the rapid development of distributed new energy,the power grid is facing enormous challenges.In order to balance the volatility of electric vehicles and the randomness of new energy output,alleviate the impact of wind and solar power abandonment and large-scale electric vehicle integration on the power grid,Monte Carlo method was used to simulate the data of electric vehicle integration.At the same time,combined with the electric vehicle load transfer strategy,the microgrid was optimized and configured,and a microgrid optimization configuration model with annual equivalent income as the optimization goal was established,and the configuration results were evaluated.The model was solved by using scene reduction method and improved particle swarm optimization algorithm.The example results demonstrate the rationality and economy of the optimized configuration model.

关 键 词：蒙特卡洛法 电动汽车 微电网优化配置 场景缩减法 改进粒子群算法 

分 类 号：TM73[电气工程—电力系统及自动化]