基于集群划分的含分散风电配电网电压调节策略

Voltage Regulation Strategy of Distribution Network with Decentralized Wind Power Based on Cluster Partition

随着大规模分布式电源的接入,配电网的电压越限问题越来越严重,传统的集中式电压控制方法已难以满足配电网控制和市场发展的需求。提出了一种基于分散风电聚类的电压调节策略,基于分布式能源的集群划分,并考虑了分散风电的有功和无功调节能力,实现集群内的功率调节和电压波动最小化的目标。在解决电压超限问题的前提下,结合优化后的PSO算法对簇内电压进行调整,所有集群调压还考虑了调压作为辅助交易的一种方式,完成全网调压。为了提高电压调节策略的电压调节效率,本文还设计了一种基于节点间电压对功率变化敏感度的分布式能量聚类划分方法,并以K均值聚类算法作为划分算法。为了优化分割结果,从初始聚类中心的选择、聚类数k值的确定和聚类中心的更新三个方面对算法进行了优化。以ieee33节点系统为例,MATLAB仿真表明,所提出的电压调节策略具有较好的优越性。

With the access of large-scale distributed energy,the voltage off-limit problem of distribution network has become more and more serious,and the traditional centralized voltage control method has been difficult to meet the demand of distribution network control and market development.In this paper,a voltage regulation strategy based on decentralized wind power clustering is proposed.Considering the active and reactive power regulation ability of decentralized wind power,based on the cluster division of distributed energy,the goal is to minimize power regulation and voltage fluctuation within the cluster.On the premise of solving the problem of voltage over-limit,combined with the optimized PSO algorithm to adjust the voltage inside the cluster.After the voltage regulation of all clusters,the auxiliary service transaction of voltage regulation shall be implemented to complete the voltage regulation of the whole network.In order to improve the voltage regulation efficiency of the voltage regulation strategy,this paper also designs a distributed energy cluster division method based on the sensitivity of voltage between nodes to power change and K-means clustering algorithm as the division algorithm.In order to optimize the partition results,the algorithm is optimized in three aspects:the selection of initial cluster center,the determination of cluster number k value and the update of cluster center.Taking ieee33 bus system as an example,the MATLAB simulation shows that the proposed voltage regulation strategy has better advantages.