Power Quality Enhancement of Grid-Connected Solar Photovoltaic System Using ANN based Filter

B. Jagadeesh
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Abstract

Grid-connected photovoltaic (PV) systems are increasingly attracting the attention of industry and academia as a means of providing an alternative to conventional fossil-fuel generation and pollution-free power. This project aims to improve the power quality level of a grid-tied PV distribution system using shunt active power filter (APF) along with adaptive current control technique. In this work Fuzzy Logic controller used to destroy the voltage and current harmonics in a grid-tied PV system. A reference current generation strategy is implemented to mitigate the current harmonics by extracting the fundamental constituents (FCs) from the nonlinear load currents. MCCF is employed to separate the FC from the distorted grid voltages and eliminates the voltage harmonics during extremely polluted grid voltage condition. The comparative analysis is analyzed to check the effectiveness of the proposed hybrid control scheme with existing and adaptive control techniques in respect of power quality, better dc offset rejection, better FC and frequency extraction, and grid synchronization.
基于神经网络滤波的并网太阳能光伏系统电能质量增强
作为一种替代传统化石燃料发电和无污染能源的方式,并网光伏系统越来越受到工业界和学术界的关注。本项目旨在利用并联电力滤波器(APF)和自适应电流控制技术提高并网光伏配电系统的电能质量水平。本文采用模糊控制器来消除并网光伏系统中的电压和电流谐波。通过从非线性负载电流中提取基波分量(fc),实现了一种参考电流产生策略,以减轻电流谐波。MCCF用于将FC与失真的电网电压分离,并消除电网电压严重污染情况下的电压谐波。通过对比分析,验证了所提出的混合控制方案在电能质量、更好的直流偏置抑制、更好的FC和频率提取以及电网同步等方面与现有的自适应控制技术的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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