利用人工神经网络和LAPO与D-STATCOM互联的性能增强光伏系统

A. Rashad, Mohamed Ebeed, S. Kamel, M. I. Mosaad
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引用次数: 1

摘要

由于太阳能电站在电网中的大量存在,研究其与相关电网之间的相互作用成为必要。本文采用分布式静态同步补偿器(D-STATCOM)来改善光伏电站在并网三相故障时的性能。采用基于闪电连接过程优化(LAPO)的人工神经网络(ANN)对目标光伏电站的D-STATCOM控制参数进行了整定。LAPO用于生成人工神经网络所需的历史数据。为了指出本文的贡献,比较了无D-SATCOM和有D-SATCOM的光伏系统在三相故障、仅用LAPO和用所提出的人工神经网络对D-STATCOM进行调谐时的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Enhancing PV System Interconnected with D-STATCOM Using ANN and LAPO
Due to the large presence of solar power plant in electric power networks, it became obligatory to study the interaction between them and the associated networks. In this paper, a Distribution Static Synchronous Compensator (D-STATCOM) is used to improve the performance of a photovoltaic generation plant (PV) during three phase fault of interconnected grid. Artificial neural networks (ANN) based on Lightning attachment procedure optimization (LAPO) is used to tune the control parameters of D-STATCOM in targeted with PV plant. The LAPO is used for generating historical data needed for ANN. In order to point out the contribution of this paper, the performance of PV system without and with D-SATCOM is compared during three-phase fault and when D-STATCOM is tuned by LAPO only and by proposed ANN.
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