基于智能模糊决策的光储系统实时调度技术  

Real-Time Scheduling Technology of Photovoltaic-Battery Generation System Based on Intelligent Fuzzy Logic Control

作　　者：邓长虹[1] 张思捷 杨威[1] 姚维为 刘正谊[1] DENG Changhong;ZHANG Sijie;YANG Wei;YAO Weiwei;LIU Zhengyi(School of Electrical Engineering,Wuhan University,Wuhan 430072,Hubei Province,China)

机构地区：[1]武汉大学电气工程学院

出　　处：《电网技术》2018年第10期3227-3233,共7页Power System Technology

基　　金：国家重点研发计划(2017YFB0903700)~~

摘　　要：实时电价作为需求侧响应项目之一,能够有效引导电力消费者参与电力市场的运行。在美国PJM电力市场的实时电价机制下,通过模糊控制器对光储联合系统进行实时调度。由于模糊控制器不具备学习能力,因此提出隶属函数变比的概念,并建立以隶属函数变比为优化变量的控制器参数优化模型,并采用智能蜂群算法进行求解。该方法不仅实现了对光储联合系统的实时调度,还能提高系统对光伏的就地消纳能力,并有效降低系统的运行成本。算例分析验证了所提方法的实时性和经济性。As a demand side response project, real-time electricity price can effectively guide electricity consumers to participate in operation of electricity market. In this paper, under real-time electricity price mechanism of PJM market in the United States, real-time scheduling of joint photovoltaics-storage system is carried out with fuzzy controller. Because fuzzy controller does not have learning ability, concept of membership function ratio is put forward. Based on variable ratio of membership function, a controller parameter optimization model is established. Then intelligent bee colony algorithm is applied to solve it. This method realizes real-time scheduling of joint photovoltaics-storage system, and reduces system operating cost by improving local photovoltaic consumption capacity of the system. A case study on MATLAB is carried out to verify real-time capability and economy of the method.

关 键 词：PJM市场 模糊逻辑控制 智能蜂群 实时调度 

分 类 号：TM721[电气工程—电力系统及自动化]