A Hybrid MPPT Controller Based on the Genetic Algorithm and Ant Colony Optimization for Photovoltaic Systems under Partially Shaded Conditions

A maximum power point tracking (MPPT) controller was used to make the photovoltaic (PV) module operate at its (MPP) under changing temperature and sunlight irradiance. Under partially shaded conditions, characteristic power–voltage (P–V) curve of PV modules will have more than one point, least local a global point. Conventional MPPT controllers may control array rather can be also implemented by using soft computing methods (SCM), which handle partial shade problem. However, improve robustness speed controller, hybrid has been proposed that combines two SCMs, Genetic Algorithm (GA) Ant Colony Optimization (ACO). Matlab in simulation GA-ACO where four SunPower SPR-305NE-WHT-D with 305.226 W connected series were conditions investigate performance controller. The results obtained analyzed compared others perturb observe (P&O) conventional ACO observed.