Data-driven optimization for reactive power operation in source distribution network without accurate modeling

被引：0
|
作者：
Gu J. [1 ]
Meng L. [1 ]
Zhu T. [1 ]
Liu S. [1 ]
Jin Z. [1 ]
机构：
[1] Research Center for Big Data Engineering and Technologies, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai
来源：
Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2021年 / 41卷 / 01期
关键词：
Data-driven; Distributed photovoltaic; Distribution network; Highway neural network; Reactive power operation optimization;
D O I：
10.16081/j.epae.202011031
中图分类号：
学科分类号：
摘要：
The access of distributed photovoltaic makes the requirement and solution of reactive power and voltage operation control for distribution network different from those of traditional distribution network. Aiming at the problems of incomplete installation of distribution network measurement equipment,difficulty in obtaining grid parameters accurately,and inability to carry out accurate mathematical modeling,a voltage optimization control model of distribution network with distributed photovoltaic is proposed without accurate modeling. Taking the qualified node voltage as the optimization goal,the highway neural network is used to fit the mapping between the injected power of grid nodes and the voltage of key nodes. Considering the output constraints of distributed photovoltaic,the directional optimization strategy and feedback mechanism are used to solve the optimization model. By changing the inverter output of distributed generation to control the grid voltage,the global system voltage control is realized. Taking the actual data of different scales of distribution networks as example,the effectiveness of the proposed optimal operation control model is veri-fied. The voltage fitting accuracy and convergence speed of the common neural network and the highway neural network are compared and analyzed,which proves that the highway neural network can be used to solve the reactive power operation problem of the multi-node source distribution network without accurate modeling,and the double optimization of fitting accuracy and fitting speed can be realized. © 2021, Electric Power Automation Equipment Press. All right reserved.
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页码：1 / 8
页数：7
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