SPLTRAK Abstract Submission
An Intelligent Algorithm for Maximum Power Point Tracking in PV Systems through Load Management
Kelvin Tan, Joseph A. Azzolini, William J. Parquette, Christian R. Polo, Meng Tao
Arizona State University, Tempe, AZ, United States

Practically all of today’s photovoltaic (PV) systems employ a maximum power point tracker (MPPT) to maximize the power output of a PV array under different temperature, weather, and irradiance conditions. We proposed and demonstrated a load-matching PV system which performs maximum power point tracking by varying the number of loads connected to the PV array, without a conventional MPPT. However, the control algorithm in our system makes many unsuccessful switches as it does not know the optimum switch points for the loads. This paper presents an intelligent algorithm that can estimate the optimum switch point before attempting a switch. Simulation and experimental results show that the proposed algorithm is effective in minimizing unsuccessful switches. These results demonstrate an improved algorithm for maximum power point tracking through load management.