Artificial intelligent controller-based power quality improvement for microgrid integration of photovoltaic system using new cascade multilevel inverter

Abstract

Nowadays, grid-connected photovoltaic (PV) power system is quite popular in many countries. For grid-connected PV power system, to achieve maximum power and good power quality of the system are considered as big challenges. In order to achieve this, artificial intelligent (AI) controller-based maximum power point tracking (MPPT) algorithm has been investigated for PV system as well as a new cascade multilevel inverter (MLI) is proposed for grid integration of PV system. The proposed cascade MLI has been designed with a smaller number of power electronic switches and it can be operated at asynchronous voltage sources, which is most adaptable for PV system. This proposed inverter can reduce the total harmonic distortion (THD) at output side by means of increasing the output voltage level with this power quality of the system has been improved. The microgrid integration of proposed inverter has been controlled by using AI-based voltage source controller and this proposed system is designed and simulated in MATLAB environment at various weather conditions and loading conditions. Finally, prototype model has been developed in laboratory and evaluating its performance. The simulation results and prototype results were verified with IEEE 1547 standard that proves the proposed system effectiveness.