考虑季节特性下的储能系统选址定容研究

Study on Location and Capacity of Energy Storage System Considering Seasonal Characteristics

风光等微电源出力的不确定性对其接入配网的安全稳定运行及电能质量带来了一定的风险隐患,而储能装置能够在一定程度上削减分布式电源并网造成的不利影响,其接入位置和容量的优化配置方案是目前亟需解决的问题。本研究以系统负荷波动、储能系统总成本、储能荷电状态偏差为目标函数,建立了储能系统选址定容优化模型;采用粒子群算法求解帕累托解集,基于信息熵的序数偏好法从帕累托解集中选取储能系统最优接入方案。考虑到不同季节下分布式电源出力特性存在较大差异,以新疆哈密地区不同季节下光伏与风电出力规律为基准,在IEEE-33节点配电系统算例分析的结果表明提议方法在求解储能系统选址定容方案中具有较好的收敛性和全局搜索能力,研究结果为储能系统选址定容方案的后续研究提供一定参考。

The uncertainty of the output of micro power sources such as wind and solar has brought certain risks and hidden dangers to the safe and stable operation of its access to the distribution network and power quality. The energy storage device can reduce the adverse impact caused by the grid connection of distributed power sources to a certain extent. The optimal configuration scheme of its access location and capacity is an urgent problem to be solved at present. Taking the system load fluctuation, total cost of energy storage system and state of charge deviation of energy storage as the objective function, this paper establishes the location and capacity optimization model of energy storage system. The particle swarm optimization algorithm is used to solve the Pareto solution set, and the ordinal preference method based on information entropy is used to select the optimal access scheme of energy storage system from the Pareto solution set. Considering that there are great differences in the output characteristics of distributed generation in different seasons, the IEEE-33 node distribution system example analysis is made based on the output laws of photovoltaic and wind power in different seasons in a region of Xinjiang Hami. The results show that the proposed method has good convergence and global search ability in solving the location and capacity determination scheme of energy storage system. These results provide some reference for the follow-up study of location and volume of energy storage system.