SOLAR ENERGY CONTROL an‎d POWER QUALITY IMPROVEMENT USING MULTILAYER FEED FORWARD NEURAL NETWORK

Oil, coal and gas continue to be the most demanded source of energy throughout the world along. In recent years, the alarming fall in amounts of fossil fuels and increase in atmospheric carbon dioxide composition have been seen on several occasions. These disadvantages of fossil fuels orientate the researchers toward renewable energy sources as a more durable long-term solution. The aim of this paper is to present a shunt active power filter (PAPF) supplied by the Photovoltaic cells ,in such a way that the (PAPF) feeds the linear and nonlinear loads by harmonics currents and the excess of the energy is injected into the power system. In order to improve the performances of conventional (PAPF) This paper also proposes artificial neural networks (ANN) for harmonics identification and DC link voltage control. The simulation study results of the new (SAPF) identification technique are found quite satisfactory by assuring good filtering characteristics and high system stability.