基于改进白鲸算法的分布式光储优化规划方法

Optimal Planning Method for Distributed Photovoltaic and Energy Storage Based on Improved Beluga Whale Optimization Algorithm

摘要:

针对分布式光伏接入配电网的选址定容规划问题，考虑并网带来的电压波动、电压越限等对电能质量的影响，通过引入储能系统来调节配电网节点电压。首先，采用迭代自组织数据分析算法，对分布式光伏出力数据进行聚类划分，并以类间相似度和类内相似度对聚类效果进行评价；然后，构建配电网两阶段优化模型：第一阶段以总成本最低为目标来考虑分布式光储的选址定容，并将规划参数代入下一阶段；第二阶段以节点电压偏移量最小和运维成本最低为目标函数，动态调节储能系统荷电状态；接着，使用改进白鲸算法求解模型，该算法引入可变螺旋搜索策略和纵横交叉策略使算法的局部寻优和全局寻优能力增强；最后，在 IEEE 33 节点下进行仿真验证。

Abstract:

Aiming at optimal siting and sizing for distributed photovoltaic (PV) access to distribution network, and considering the impacts of voltage fluctuation and voltage overlimit brought by grid connection on power quality, the voltage at distribution network nodes is regulated by introducing energy storage system. Firstly, an iterative self-organizing data analysis algorithm is employed to cluster the output data of distributed PV, and the clustering performance is evaluated based on between-class similarity and within-class similarity. Secondly, a two-stage optimization model for distribution network is established: the first stage aims to minimize the total cost by considering the siting and sizing of distributed PV and energy storage, and the planning parameters will be passed to the second stage; the second stage takes minimum node voltage deviation and minimum operation and maintenance costs as objective function. And then, the Beluga whale optimization algorithm is applied to solve the model, which incorporates variable spiral search strategy and crisscross strategy to enhance its local and global optimization capabilities. Finally, simulation verification is carried out on IEEE 33-node system.