Operation and Control Strategy of Wind/Photovoltaic System with Battery Storage using Neural Networks

This paper presents the design and operation of the multisource hybrid windphotovoltaic system with energy management strategy using Neural Networks. Unlike conventional generation, the wind and sunrays are available at no cost and generate electricity pollution free and also it requires very low maintenance. The proposed energy management strategy was simulated in MATLAB/Simulink with the Neural Network controller. The optimal transfers of power from the sources are based on power, voltage and current control was done in order to regulate the DC bus voltage to a fixed value. The various models of the output waveforms are represented and discussed. The role of Neural Network controller is to interconnect the system for optimal performance based on expected wind, solar irradiations and battery voltage. The Neural Network controller takes the input from Solar (irradiation), Wind (speed) and the battery status of charge and controls the respective subsystem which formulates into different operational modes of energy management and the proposed system have very high accuracy and efficient operation which leads to a reduced operating cost.