Study of reactive power compensation based on neural network

被引：0

作者：

Xiong Chao ^{[1
]}

Li Chunlai ^{[2
]}

Yang Libin ^{[2
]}

Li Xin ^{[1
]}

Hui Qian ^{[1
]}

Teng Yun ^{[1
]}

机构：

[1] Shenyang Univ Technol, 111 Shenliao West Rd, Shenyang 110870, Peoples R China

[2] Qinghai Elect Power Res Inst, Xining 810008, Peoples R China

来源：

PROCEEDINGS OF THE 35TH CHINESE CONTROL CONFERENCE 2016 | 2016年

关键词：

Renewable energy; reactive power compensation; Harmonic Detection; Neural Networks;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

As a promising renewable alternative, a significant contribution to a photovoltaic power generation system in the future, but also brought new problems related to the integration of power quality, including voltage control and reactive power compensation. This study proposes a new adaptive neural network DC / AC converter-based control. In this study, the use of neural network control to increase the DC / AC converter transient response. Aiming at these problems, explore the effect of reliability and power quality and reactive power compensation system optimization, and propose coherent active and reactive power distribution in order to alleviate this problem. In an area of photovoltaic power plant simulation. Simulation results verify the effectiveness of the method. The results show that the proposed method helps to achieve this adaptive control.

引用

页码：3690 / 3693

页数：4

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