Bat algorithm based maximum power point tracking for photovoltaic system under partial shading conditions

Abstract

This paper presents a maximum power point tracking (MPPT) method for photovoltaic system under partial shading conditions using bat algorithm (BA). The bat algorithm is a swarm intelligence based method which was inspired by the echolocation behaviour of bats. BA have a high accuracy in the global optimisation and it can provide good dynamic performance and very quick convergence rate by automatically switching between exploration and exploitation stages during the MPPT process. To verify the performance of the proposed method, several simulations have been carried out in Matlab/Simulink environment for various shading patterns. The simulations results highlight the accuracy of the proposed scheme for optimal management of the energy available at the output of the photovoltaic panels. In addition, the comparison with the P&O and the PSO methods shows that the proposed method outperforms them in term of global search ability and dynamic performance. To verify the practical implementation of the proposed method, a modular reconfigurable architecture is designed using very high speed integrated circuit hardware description language (VHDL) and implemented on Xilinx Virtex-5 (XC5VLX50-1FFG676) Field Programmable Gate Array (FPGA). The use of FPGA for designing the MPPT controller provides high performance, increases the robustness and makes the hardware implementation more flexible. The algorithm is tested in real time application on a buck-boost converter using a real photovoltaic panel. Experimental results confirm the efficiency of the proposed method in the global peak tracking and its high accuracy to handle the partial shading.