A Stand Alone Hybrid Power Generation System by MPPT Control Based on Neural Networks

Abstract

Hybrid Power Generation system with neural networks is proposed in this paper. The system consists of Wind Power, Solar power, Diesel Engine and an Intellectual controller. MATLAB2009b/Simulink was used to build the dynamic model and simulate the system. Here Maximum Power Point Tracking (MPPT) control is attained by Intellectual controller. It consists of Radial Bias Function Network (RBFN) and Modified Elman Neural Network (MENN). The pitch angle of wind turbine is controlled by the MENN and the solar system uses RBFN, where the output signal is used to control the dc/dc boost converters to achieve the MPPT. A Modified ENN and RBFN is used to control MPPT and to reduce the Total Harmonic Distortion (THD) in the Grid.