Scholarlink

<p>This paper presents a novel framework for enhancing grid integration in hybrid photovoltaic (PV)-wind systems using an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based Distributed Power Flow Controller (DPFC). The proposed system addresses the dynamic challenges of hybrid renewable energy sources, optimizing power flow and improving grid stability. By integrating Maximum Power Point Tracking (MPPT) techniques, the system maximizes efficiency, while the ANFIS-based controller ensures adaptive management of voltage and current, reducing harmonic distortions. Simulation results demonstrate that this approach offers superior performance compared to traditional control methods, enhancing both system reliability and energy distribution quality.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Enhanced grid integration in hybrid power systems using ANFIS-based distributed controllers

  • 期刊论文

  • 发表日期：

    2025年1月16日

查看全文
  • Srinivasa Acharya,
  • D. Vijaya Kumar,
  • Rajana Venu,
  • Bantupilli Rajasekhar,
  • Gorinta Rohini,
  • Reddi Sathvika

摘要

This paper presents a novel framework for enhancing grid integration in hybrid photovoltaic (PV)-wind systems using an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based Distributed Power Flow Controller (DPFC). The proposed system addresses the dynamic challenges of hybrid renewable energy sources, optimizing power flow and improving grid stability. By integrating Maximum Power Point Tracking (MPPT) techniques, the system maximizes efficiency, while the ANFIS-based controller ensures adaptive management of voltage and current, reducing harmonic distortions. Simulation results demonstrate that this approach offers superior performance compared to traditional control methods, enhancing both system reliability and energy distribution quality.