摘要
光伏、储能和需求侧响应的协调运行可有效平抑负荷波动并提升配电网运行的经济性。针对需求响应下光伏微电网储能电池的协调优化问题,基于分时电价的储能电池需求响应,采用BP神经网络以配置光储容量,并引入粒子群算法(particle swarm optimization,PSO)优化BP神经网络,用以预测光伏出力,改善BP神经网络性能。最后构建了以用户用电成本最小化为目标的储能运行策略和容量配置的协同优化模型,通过MATLAB验证了模型的有效性,为电池储能系统在电网需求侧辅助服务市场中的应用提供技术支撑。
Coordinated operation of PV,energy storage and demand side response can effectively suppress load fluctuation and improve the economy of distribution network operation.The BP neural network was adopted to configure optical storage capacity,based on the demand response of energy storage batteries of the time-of-use electricity price to solve the problem of coordination and optimization of PV micro-grid energy-saving batteries under demand response.Furthermore,the Particle Swarm Optimization(PSO)algorithm was introduced to optimize the BP neural network for PV output forecasting and improvement of the performance of the BP neural network.Finally,a coordinated optimization model for the energy storage operation strategy and capacity configuration,aiming at minimization of users’electricity cost.Matlab simulation verified the validity of the model,thus providing technical support for the application of the battery energy-saving system to the auxiliary service market atg the grid demand side.
作者
刘文轩
宋璇坤
韩柳
陈旭海
陈佳桥
Liu Wenxuan;Song Xuankun;Han Liu;Chen Xuhai;Chen Jiaqiao(State Grid Economic and Technological Research Institute Co.,Ltd.,Beijing 102209,China;China Power Construction Group Fujian Electric Power Survey and Design Institute Co.,Ltd.,Fuzhou Fujian 350003,China)
出处
《电气自动化》
2020年第5期22-24,79,共4页
Electrical Automation
基金
国网经济技术研究院有限公司自主投入科技项目(524415190001)“基于源网荷储耦合模式的储能电站设计及控制技术研究”
福建省科学技术厅引导性项目(2019H01010204)“百兆瓦时级大规模锂电池储能站关键技术研究及示范应用”。
关键词
光伏
储能
微电网
需求响应
负荷预测
协调优化
photovoltaic
energy storage
micro-grid
demand response
load forecasting
coordination and optimization
