Optimal Performance of Novel Hybrid Harmony Search Optimization based Maximum Power Tracker Solar PV

Abstract

In today's quickly evolving renewable energy sector, increasing photovoltaic (PV) system efficiency is crucial, especially as we struggle with growing power demands and seek to diminish the negative impacts of traditional fossil fuels. A novel optimisation method for maximum power point tracking (MPPT) in photovoltaic (PV) systems is highlighted in this article. It is based on the Hybrid Harmony Search (HHS) method and will be directly contrasted with two conventional approaches, Perturb and Observe (P&O) and Particle Swarm Optimisation (PSO). MPPT is an efficiently operated method for improving PV system performance, especially under variations in the environmental conditions where shading occurs and PSD often leads to slow convergence and high sensitivity to parameters, so the proposed novel HHS-based method was developed because of its inherent adaptability and general global search approach to quickly and accurately identify the global maximum power point (MPP). Utilizing MATLAB/Simulink to assess the performance of the proposed HHS-based methods over a range of varying conditions, the results were put in an extensive comparison between the P&O and PSO methods on the designed approaches for test system operation. HHS is known to converge and have better yield convertibility versus traditional particular tracking methods because it combined of  the advantage of PSO and DE thus proposed methods identified as a high comparability on real-time optimization processing on Solar PV systems.