Investigation And Analysis of Solar Energy Generation with Machine Learning Techniques

Abstract

It is necessary for India to develop alternative energy sources in order to reduce its reliance on imported oil in order to attain energy stability. Furthermore, India's average per capita energy consumption is much lower than that of industrialised nations. The same is anticipated to increase substantially as a result of the fast economic growth and the possibility for fast industrialization that has occurred. Developing countries may benefit significantly from the use of sustainable renewable energy sources in the industrialization and development of their own countries. The overall demand for fossil fuels is expected to rise substantially in the near future as a consequence of continued industrial and economic expansion. Renewable Energy will not only assist India's energy supply, but they will also aid the nation in its battle against climate change. As a consequence of increased yields from carbon dioxide reduction permits under clean growth management, the feasibility of renewable energy sources is further enhanced. Overall, the clean energy industry, as well as the variety of uses for clean energy, has evolved and grown significantly in recent years. This paper examines the electricity generated by thermal generation, nuclear generation, and hydroelectric generation between 2017 and 2020. On the basis of secondary resources, the exploration is conducted. It is the primary goal of this study- data and display the data in a comprehensible manner. This study is also being used to the solar data in order to analyse the performance of the power system in time series and the loss over time. In this case, solar data from Kaggle was used in conjunction with a Python simulator. As a component of machine learning methods (ML-Algorithms), a neural network has been used to conduct data processing in time slices, and the loss and mean square error have been calculated in a certain time phase to evaluate solar energy and production as a power producing system. Overall, this research explores the photovoltaic cell, radiation patterns of solar energy generation.