A New Modified Artificial Neural Network Based MPPT Controller for the Improved Performance of an Asynchronous Motor Drive

To improve the performance of asynchronous motor drive, the proposed Artificial Neural Network (ANN) based Maximum Power Point Tracking (MPPT) controller has been used to fed the asynchronous motor drive with the obtained output voltage and currents of PV MPPT. Methods and Analysis: DC-DC boost converter and space vector modulation technique inverter are used to provide the required supply to the load. The proposed ANN based MPPT improves the system efficiency even at abnormal weather conditions. Findings: Solar energy is an important alternative out of the various renewable energy sources. On an average the sunshine hour in India is about 6hrs per day also the sun shines in India is about 9 months in a year. To generate electricity from the sun, the Solar Photo Voltaic (SPV) modules are used. The SPV comes in various power outputs to meet the load requirements. Maximization of power from a solar photo voltaic module is a special case to increase the efficiency of the system. The proposed artificial neural network (ANN) based MPPT controller is used to track the maximum power. DC-DC boost converter and space vector modulation technique inverter are used to provide the required supply to the load. The proposed ANN based MPPT improves the system efficiency even at abnormal weather conditions. Torque and current ripple contents have been reduced to a large extent with the help of proposed ANN based MPPT for an asynchronous motor drive. Also the better performance of an asynchronous motor drive is analyzed by the comparison of existed conventional and proposed MPPT controller using Matlab-simulation results. Improvement: Improvements in torque and current ripple and better speed performances are clearly analyzed with the help of practical validations. And also few of the observations are carried out and tabulated.