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PVs (photo Voltaics) are the leading player in distributed power systems. Despite all the developments and evolution, the affordability of the solar system is still challenging. The issue of its economy has led to the development of Maximum PowerPoint Tracking (MPPT). The role of maximum power extraction under partial shading is a crucial feature of energy harvesting. This paper has reviewed various conventional, soft computing, and hybrid techniques for MPPT under partial shading conditions. It is observed that conventional methods fail to extract maximum power under partial shading conditions due to multiple peaks. Therefore, different soft computing, hybrid techniques, algorithms and modern PV topologies are discussed to track global maxima from multiple local maxima. The strengths and weaknesses of various methods' tracking speed, transient and steady-state oscillation, cost, computational complexity, etc., are taken as independent quantities and various MPPT techniques as dependent quantity to prepare a user-friendly table. Also, three different meta-heuristic algorithms (Cuckoo Search, JAYA and PSO) performance have been compared for the PSC based on tracking time and efficiency by using a Hardware-in-the-loop (HIL) simulation platform. [ABSTRACT FROM AUTHOR]

This paper introduces a novel approach that extracts the maximum power from photovoltaic (PV) system utilizing the Horse Herd Optimization (HHO) algorithm under different weather conditions, including fast changes in solar radiation (FCSR) and partial shading conditions (PSCs). The HHO algorithm is a technique for optimization that mimics the movement behavior exhibited by horses within a herd. The proposed MPPT controller has been tested and compared with other recognized metaheuristic algorithms, including the Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), Flower Pollination (FP), Deterministic PSO (DPSO), and Cuckoo Search (CS). According to the simulation results, the proposed HHO-based MPPT method is found to outperform other considered metaheuristic methods in terms of the maximum power extraction, fast-tracking, and settling times under various weather conditions. Additionally, the suggested MPPT controller is robust and can continuously track the MPP under the FCSR. The performance of the proposed HHO controller is validated experimentally on a real PV system. It is demonstrated that the proposed HHO algorithm is robust and capable of outperforming the other counterpart metaheuristic algorithms as well as offering the highest MPPT efficiency of about 98.81 % with a rapid tracking time of 2.2 s. Furthermore, it has the lowest power oscillations of about 1.91 %, ensuring stable and consistent power output. [ABSTRACT FROM AUTHOR]