The maximization of photovoltaic power is a crucial task, particularly under abnormal shading conditions for the creation of various problems such as hotspots, shading effects, dust accumulation, aging, and others. This chapter covers the application of optimization methods based on artificial intelligence techniques for maximizing the photovoltaic output power under uniform and non-uniform solar conditions. The material presented mainly focuses on the application of fuzzy logic, neural networks, neuro-fuzzy, particle swarm optimization, and various hybrid combinations of these techniques. There are mainly two ways for maximizing the PV output power: (1) by tracking the maximum power from a photovoltaic array using maximum power tracking algorithms and (2) by photovoltaic array reconfiguration (static or dynamic techniques), which are globally used to prevent shading effects. Eight examples are presented in detail using Matlab®/Simulink.
Handbook of Artificial Intelligence Techniques in Photovoltaic Systems: Modeling, Control, Optimization, Forecasting and Fault Diagnosis, 2022, Pages 149-182,