NEURO-FUZZY MODELING AND MPPT CONTROL OF PHOTOVOLTAIC ARRAYS FEEDING VSI INDUCTION MOTOR DRIVES

Abstract

The paper presents a maximum power point tracking (MPPT) approach and a modeling technique for photovoltaic (PV) arrays feeding voltage-source inverter (VSI) induction motor driving a water pump load. The proposed methodology is based on adaptive neuro-fuzzy inference systems (ANFIS) employed to obtain the chopper duty ratio which guarantees maximum power operation, and to model the PV array. A pilot module of the array is periodically tested to estimate the solar irradiation and cell temperature to avoid the high cost and technical difficulties of direct measurement. Results show that maximum power operation was maintained under different loading and environmental conditions with acceptable performance of the induction motor drive.