考虑负荷不确定性的配电网分层协调控制策略
摘要:忽视配电网运行的负荷特点，会导致蓄电池状态以及功率交换情况的优化不足。为了解决配电网节点拓扑和负荷不确定性的问题，提出了一种考虑负荷不确定性的配电网分层协调控制方法。分析了包括负荷节点、变压器、断路器、隔离开关等节点在内的配电网拓扑结构，分别计算了并网模态、孤岛模态下的能量关系，建立源网荷储分层协调控制模型，并使用拉丁超立方抽样方法生成不确定性的场景，引入了惯性权重、学习因子等参数改进粒子群算法，设计多目标分层粒子群算法的调控流程，实现配电网源网荷储分层协调控制。实验结果表明：应用该方法后，蓄电池的能量状态更好，交换功率更高；分层协调控制效果较佳，并可以根据实际需求进行配电网负荷状态自适应调整。
Abstract：Ignoring the load characteristics of distribution network operation will lead to insufficient optimization of battery state and power exchange. In order to solve the problems of distribution network node topology and load uncertainty, a hierarchical coordination control method for distribution network considering load uncertainty is proposed. The topological structure of distribution network including load node, transformer, circuit breaker, isolation switch and other nodes is analyzed, and the energy relationship under grid-connected mode and island mode is calculated respectively, and the hierarchical coordination control model of source, network, load and storage is established. In addition, Atin hypercube sampling method is used to generate uncertain scenes, and parameters such as inertia weight and learning factor are introduced to improve the particle swarm optimization algorithm, and the regulation process of multi-objective layered particle swarm optimization is designed to realize the layered coordinated control of load and storage in the source network of the distribution network. The experimental results show that the energy state of the battery is better and the exchange power is higher after the method is applied. The effect of hierarchical coordination control is better, and the load state of distribution network can be adjusted adaptively according to the actual demand.
标题：考虑负荷不确定性的配电网分层协调控制策略
title:Layered Coordination Control of Distribution Network Considering Load Uncertainty
作者：王伟,孙夏,郭俊,姜伟,孙哲彬,刘鹏宣
authors:WANG Wei,SUN Xia,GUO Jun,JIANG Wei,SUN Zhebin,LIU Pengxuan
关键词：节点拓扑,负荷不确定性,配电网,分层协调控制,粒子群算法,
keywords:node topology,load uncertainty,distribution network,hierarchical coordination control,particle swarm optimization algorithm,
发表日期：2024-05-15
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