利用自适应神经模糊推理系统(ANFIS)控制器增强静态无功补偿器(SVC)缓解次同步共振

M. Amirian
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引用次数: 6

摘要

目前,可再生能源,特别是风力发电,由于其不枯竭的特性和良好的环境效应,被认为是电力系统中的重要发电方式。随着风电在电力系统中的应用日益增加,风力发电机组对次同步谐振的影响越来越重要。本文的主要目的是确认静态无功补偿器(SVC)作为FACTS家族的一员在减轻SSR的能力。为了给SSR系统提供有效的阻尼,设计了基于帝国主义竞争算法(ICA)的传统阻尼控制器(CDC)和自适应神经模糊推理系统(ANFIS)。通过时域仿真、快速傅立叶变换(FFT)分析和基于电力系统动态特性定义的性能指标(PI)来研究系统的稳定性。为了比较两个控制器的性能,考虑了两个不同的研究案例。
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Mitigating Sub-Synchronous Resonance Using Static Var Compensator (SVC) Enhanced with Adaptive Neuro-Fuzzy Inference Systems (ANFIS) Controller
Nowadays renewable energy sources, particularly wind power, are considered as important generation in electric power systems because of their no exhausted nature and benign environmental effects. With increasing usage wind power in power systems, impact of wind generator on sub-synchronous resonance (SSR) is going to more important. The main purpose of this paper is to confirm the ability of the Static Var Compensator (SVC) as a member of FACTS family in mitigating the SSR. Imperialist competitive algorithm (ICA)-based Conventional Damping Controller (CDC) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS) are designed as two novel controllers In order to provide the effective damping of SSR. The system stability is studied through time domain simulations, Fast Fourier Transform (FFT) analysis and a Performance Index (PI) which is defined based on the dynamics of the power system. To compare the performance of two controllers, two various cases of study are considered.
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