Solar Power Generation System Based on Signal Search Artificial Bee Colony Optimization Algorithm for Maximum Power Point Tracking

Photovoltaic (PV) systems used for the generation of power have been encouraged due to the availability and reliability of solar energy. A designed control system for the generation of power based on solar using a signal search artificial bee colony (SS-ABC) optimization algorithm as the maximum power point tracker (MPPT). The shorter and longer distances between the bees and their prey are signaled using the SS-ABC. The quick concurrence and high accuracy of the SS-ABC are established as it interactively integrates with the exploratory evolution with the essential distinctive signal search from the PV array during the maximum power point tracking process which increases the speed and tracks more power. The SS-ABC was compared with conventional ABC, particle swarm optimization (PSO), bat algorithm (BA), and perturb and observe (P&O) algorithms. The design was implemented and simulated in MATLAB Simulink and the efficiency of the proposed method has been achieved from the results.