Intelligent Partition Strategy of Distributed Photovoltaic Cluster in Distribution Network Based on SLM-RBF

被引:0
|
作者
Bu, Qiangsheng [1 ]
Lü, Pengpeng [1 ]
Li, Weiqi [2 ]
Luo, Fei [1 ]
Yu, Jingwen [2 ]
Dou, Xiaobo [2 ]
Hu, Qinran [2 ]
机构
[1] Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd., Nanjing,210000, China
[2] School of Electrical Engineering, Southeast University, Nanjing,210096, China
关键词
Boolean functions - Electric load flow - Power distribution networks;
D O I
10.16183/j.cnki.jsjtu.2023.032
中图分类号
学科分类号
摘要
Access of large-scale distributed power supply to the distribution network brings dimensionality disaster to the optimal dispatching of the distribution network. Therefore, it is necessary to cluster the distributed power supply to rcduce the difficulty of regulation and control, and a reasonable division of distributed power supply cluster is very important. Howevcr, the incomplete real-time measurement data of the distribution network has caused difficulty and low time efficiency in real-time cluster division of the distribution network. Therefore, this paper proposes a distributed power cluster division strategy based on the smart local moving (SLM) algorithm and the radial basis function (RBF) neural network. First, the ränge of activc power and reactive power regulation and the sensitivity of active power and reactive power to voltage are selected as the indexcs of cluster division. By constructing a similarity matrix, the SLM algorithm is used to form the historical strategy library of clustcr division of distributed power sources. Then, a voltage fitting model is established offline, which can observe the relationship between the power and voltage of buses in real time. Meanwhile, a voltage-division rcsult model is established offline, and the real-time division result is obtained through the voltage online, which solves the problem that cluster division cannot be performed when the power flow model is missing, and improvcs the real-time Performance of clustcr division. Finally, the rationality and superiority of the algorithm are verified by Simulation on MATLAB platform. © 2024 Shanghai Jiaotong University. All rights reserved.
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页码:1534 / 1543
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