The Athletics Running Algorithm-Based Improved Incremental Conductance Method for Photovoltaic Power Systems Under Partial-Shading Conditions: The Athletics Running Algorithm Based on Improved Incremental Conductance Method for PV Power Systems Under PSCS

Utilizing the description of a short-distance running race, this article introduces an uncomplicated, revolutionary method for locating the greatest power peak in photovoltaic (PV) power systems. The active-region splitting of players at the starting line acts as the foundation for the operating principle of this strategy. The duty-ratio parameters used to regulate the dc boost converter are matched up for each location of the contestant. The athletics running algorithm-based improved incremental conductance (ARAIIC) method will be used to estimate the duty-ratio value that will allow the load to acquire the most electrical power from the PV system. The global maximum power point (MPP) may be precisely determined with the use of contemporary regional division concepts and up-to-date locations. The outcomes of the simulations and experiments revealed that the proposed method had a high degree of efficiency in comparison to the particle swarm optimization (PSO) and grey wolf algorithm (GWA) approaches. In comparison to the PSO and GWA approaches, which take between 0.7 and 0.85 s and 0.8 to 0.85 s, respectively, that monitor the global MPP effectively, the suggested method has successfully done so between 0.45 and 0.52 s. The gathered results revealed that the ARAIIC approach was superior and more effective than what had been recommended. In terms of excellent transient oscillation and a global MPP tracking (MPPT) time of 0.76–0.78 s, the suggested technique has a reaction time between 0.02 and 0.12 s faster than the PSO and GWA methods.