Scholarlink

Among the most prominent sources of alternative power in recent years is solar energy. Thus, photovoltaic (PV) systems need to be made more efficient and reliable. A PV panel’s conversion capacity is between 23% and 24% when it converts solar energy to electricity. However, the average conversion efficiency for most PV panels was around 15–20%. Identifying the maximum power point (MPP) on PV panels is one way to increase conversion efficiency. MPPT system control is presented and discussed in this paper for a 100 MW system in Metehara, Ethiopia. The aim of this paper is to present a novel hybrid approach for maximum power point tracking (MPPT). A particle swarm optimization (PSO) algorithm and a P&O MPPT technique are combined in this method. In order to achieve the MPP with improved speed and accuracy, the algorithm goes through a series of stages. MATLAB/Simulink was used to model the proposed algorithm under different operating conditions. Through comprehensive simulations across diverse input conditions, the proposed approach’s MPP tracking performance is assessed. When compared with systems lacking MPPT techniques, the hybrid approach demonstrates an average efficiency of 99.76%.

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

Simulation of a 100 MW Grid-Connected Solar Power Plant and MPPT Control Using the PSO-P&O Technique

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Betelhem Dereje Bruk,
  • Fekadu Shewarega,
  • Birhanu Hailu Belay,
  • Mezigebu Getinet Yenealem,
  • Dereje Shiferaw Negash

摘要

Among the most prominent sources of alternative power in recent years is solar energy. Thus, photovoltaic (PV) systems need to be made more efficient and reliable. A PV panel’s conversion capacity is between 23% and 24% when it converts solar energy to electricity. However, the average conversion efficiency for most PV panels was around 15–20%. Identifying the maximum power point (MPP) on PV panels is one way to increase conversion efficiency. MPPT system control is presented and discussed in this paper for a 100 MW system in Metehara, Ethiopia. The aim of this paper is to present a novel hybrid approach for maximum power point tracking (MPPT). A particle swarm optimization (PSO) algorithm and a P&O MPPT technique are combined in this method. In order to achieve the MPP with improved speed and accuracy, the algorithm goes through a series of stages. MATLAB/Simulink was used to model the proposed algorithm under different operating conditions. Through comprehensive simulations across diverse input conditions, the proposed approach’s MPP tracking performance is assessed. When compared with systems lacking MPPT techniques, the hybrid approach demonstrates an average efficiency of 99.76%.