A Soft Computing Intelligent Control Algorithm to Extract Maximum Energy from Solar Panel

Abstract

Utilizing soft computing, a maximum power point tracking (maximum PPT) control algorithm is developed, and its performance is compared to that of more traditional Lead Acid battery charging methods such as incremental conductance technique-based maximum PPT. Since the power vs voltage graph of a photovoltaic (PV) cell is nonlinear, a suitable control method seeks to obtain the highest power under dynamic conditions. In order to construct a PV cell with the maximum PPT, a fuzzy logic control approach known as soft computing is used. The cell active energy is used to charge the lead acid battery. A fuzzy logic compares its performance with the incremental conductance technique under dynamic conditions. Moreover, dc to dc converter is required to maintain constant output voltage to charge the battery under low level voltage. A zeta converter is taken to maintain output voltage under various insolation. The significance of algorithm is demonstrated by MATLAB Simulation results and hardware results.

Keywords

• incremental conductance
• lead acid battery
• soft computing
• solar pv system
• zeta converter