Determination of Power Losses in Solar Panels Using Artificial Neural Network

ABSTRACT: The world’s traditional energy resources remain insufficient with respect to the increasing energy requirements of the modern era. In recent decades the threats and limitations associated with energy resources such as fossil fuels have motivated researches to find alternative clean and sustainable energy resources. Concentrated solar power is considered as one of the most competitive and rapidly growing renewable energy resources which emerge to meet the modern world’s increasing energy requirements. Along with the rising demand for alternative energy resources, the technologies and methods regarding utilization of solar energy have been the subject of many scientific works recently. Solar panels made of solar cells generate electrical power from sun’s radiations and developing management and controlling techniques for solar panels plays a major role in benefitting from solar energy. The purpose of this study is to develop an intelligent fault detection system which provides possibilities of real time monitoring and fault detection of solar panels. Utilizing artificial neural network technology, the intelligent solar panel fault detection system is capable of perceiving sun’s position in the sky and estimating the corresponding output power of a solar panel based on algorithms derived by the artificial neural network which has been trained on solar data at several time intervals. The system being capable of operating in any geographical location provides possibilities of 24-hour monitoring and fault detection as well as future power estimations for solar panels. Keywords: Renewable Energy, Photovoltaic, Solar Energy, Solar Panel/Cell, Intelligent Fault Detection, Artificial Neural Network, Output Power Estimation. …………………………………………………………………………………………………………