Fuzzy Neural Network Based Optimal and Fair Real Power Management for Voltage Security in Distribution Networks with High PV Penetration

被引：4

作者：

Yang, Jindong ^{[1
]}

Luo, Junyuan ^{[2
]}

Zhang, Haitao ^{[2
]}

机构：

[1] Yunnan Power Grid Elect Power Res Inst, Kunming, Yunnan, Peoples R China

[2] Lincang Power Supply Co, Lincang, Yunnan, Peoples R China

来源：

JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY | 2020年 / 15卷 / 06期

关键词：

Distributed generation; Distribution network; Optimal dispatch; Photovoltaic; Voltage regulation;

D O I：

10.1007/s42835-020-00527-1

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The high penetration of distributed generation (DG) sources in distribution networks (DN) can induce overvoltage issues. In this paper, an artificial intelligence based fair and optimal method for voltage regulation in DN with high photovoltaic (PV) penetration is proposed. Based on the forecasting of solar radiance and load profiles, the method optimally dispatches the generation of PVs to prevent overvoltage with the objective of minimizing the energy curtailment of PVs for a given long period. In addition, the RPCM can adaptively adjust the curtailment of PVs based on fuzzy neural network algorithm so that the PV systems in the DN could reach and keep similar accumulated curtailments during the period. Steady state simulation studies under various scenarios have been carried out on a 69-bus distribution feeder and an actual distribution network to demonstrate the effectiveness of the proposed method.

引用

页码：2471 / 2478

页数：8

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