Fuzzy embedded MPPT modeling and control of PV system in a hybrid power system

Abstract

The literature is populated with different Maximum Power Point Tracking (MPPT) methods for Photovoltaic (PV) system to obtain maximum power from it. This piece of work provides an artificial intelligence-based fuzzy logic MPPT modeling and control of PV system in a grid connected hybrid power system under different weather patterns. The proposed technique uses seven fuzzy sets with seven linguistic variables applied to a DC-DC converter. Furthermore, a battery module is added as an energy storage system during surplus power and/or backup device during load demand. The overall operation of system is performed by classical logic power management switching algorithm. The performance of proposed method is compared with and without Proportional Integral Derivative (PID) MPPT controllers. MATLAB simulation results show better behavior of proposed method in terms of load tracking and reliability.