Scholarlink

<p>The effective tracking of maximum power point (MPP) is one of the most essential aspects for Solar Photovoltaic (PV) system. It becomes even more significant in the cases where panels are shaded and conditions are varying. In this paper a detailed analysis of preferred MPPT algorithms like Perturb &amp; Observe (P&amp;O) and Particle Swarm Optimization (PSO) have been performed for shaded panels and compared with the proposed Flower Pollination Algorithm (FPA) based methodology. The tracking capability under partial shading phenomena has been thoroughly investigated where shading percentage is varied and different performance indices like accuracy in tracking global maxima, convergence speed, oscillations and efficiency are verified. According to simulation findings, it is demonstrated that the P&amp;O method stuck up tracking the local peak resulting in considerable power loss whereas both PSO and FPA when tested under three different shading patterns were found to be capable of obtaining the maximum possible power (global peak power). However, the tracking speed of proposed FPA methodology is found to be higher than PSO. Further, as the percentage of shading increases, this difference in convergence time becomes more and more significant with FPA algorithm superseding the PSO substantially. Thereby FPA lowers the power loss due to misrecognition of the local power point and enhances PV power generation efficiency. The results obtained strongly suggest that the proposed FPA is highly effective, efficient and faster approach in comparison to other algorithms for tracking MPP under partial shading conditions.</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

Application of Flower Pollination Algorithm and its Comparative Analysis for MPPT of Solar Panels Under Partial Shading Conditions

  • 期刊论文

  • 发表日期：

    2025年1月27日

查看全文
  • Jahid,
  • Md Ehtesham,
  • Sheeraz Kirmani,
  • Manaullah

摘要

The effective tracking of maximum power point (MPP) is one of the most essential aspects for Solar Photovoltaic (PV) system. It becomes even more significant in the cases where panels are shaded and conditions are varying. In this paper a detailed analysis of preferred MPPT algorithms like Perturb & Observe (P&O) and Particle Swarm Optimization (PSO) have been performed for shaded panels and compared with the proposed Flower Pollination Algorithm (FPA) based methodology. The tracking capability under partial shading phenomena has been thoroughly investigated where shading percentage is varied and different performance indices like accuracy in tracking global maxima, convergence speed, oscillations and efficiency are verified. According to simulation findings, it is demonstrated that the P&O method stuck up tracking the local peak resulting in considerable power loss whereas both PSO and FPA when tested under three different shading patterns were found to be capable of obtaining the maximum possible power (global peak power). However, the tracking speed of proposed FPA methodology is found to be higher than PSO. Further, as the percentage of shading increases, this difference in convergence time becomes more and more significant with FPA algorithm superseding the PSO substantially. Thereby FPA lowers the power loss due to misrecognition of the local power point and enhances PV power generation efficiency. The results obtained strongly suggest that the proposed FPA is highly effective, efficient and faster approach in comparison to other algorithms for tracking MPP under partial shading conditions.