Reactive Power Optimization of Distribution Network Based on Data-driven Method

被引：0

作者：

Cai C. ^{[1
,2
]}

Cheng Z. ^{[1
,3
]}

Zhang G. ^{[4
]}

Li Y. ^{[1
,3
]}

Chu Y. ^{[1
,2
]}

机构：

[1] Jiangsu Key Laboratory of Power Transmission & Distribution Equipment Technology, Hohai University, Jiangsu Province, Changzhou

[2] College of Artificial Intelligence and Automation, Hohai University, Jiangsu Province, Changzhou

[3] College of Information Science and Engineering, Hohai University, Jiangsu Province, Changzhou

[4] Changzhou Power Supply Company, State Grid Jiangsu Electric Power Co., Ltd., Jiangsu Province, Changzhou

来源：

Dianwang Jishu/Power System Technology | 2024年 / 48卷 / 01期

基金：

中国国家自然科学基金;

关键词：

active control; automatic encoder; data driven; deep extreme learning machine; reactive power optimization;

D O I：

10.13335/j.1000-3673.pst.2022.1707

中图分类号：

学科分类号：

摘要：

There are new challenges for the traditional reactive voltage control in computing speed and accuracy with the high penetration of distributed generation, energy storage and flexible load in the distribution network. In this paper, a data-driven reactive voltage control method is proposed for the control of the reactive voltage by tracking the operating parameters of the actual system. An auto encoder is combined into the extreme learning machine to construct a deep learning mechanism, and the direct coupling relationship between the input and output of the extreme learning machine is established based on the automatic encoder. The unsupervised learning and the supervised learning are comprehensively integrated to reduce the iterative process of the training model in the deep extreme learning machine. Then, a series of distribution network operation scenarios based on the distributed power supply and flexible load prediction information are built using the Monte Carlo method. The deep extreme learning machine is used to mine the internal relationship between the optimal operation in the operation scenarios and the status of the reactive voltage regulators. The mapping relationship between the grid operation scenarios and the reactive power voltage regulation strategies of the system is established. The proposed method realizes the tracking of the distribution network operation state and the optimal scheduling of reactive power regulation equipment without depending on the actual system power flow calculation, providing a support for the reactive voltage control. © 2024 Power System Technology Press. All rights reserved.

引用

页码：373 / 382

页数：9

共 20 条

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