Today's world requires extremely efficient energy consumption. Demand is rising as a result of the industrial sector's quick advancements, making energy efficiency initiatives essential to reducing energy waste and satisfying demand. According to the study of numerous scenarios utilized by policy makers, at least a 50% reduction in industrial energy use is required for the world temperature to rise by less than 2°C by the end of this century. It is crucial that, we include a trustworthy forecasting tool that can be used to estimate the energy consumption based on numerous anticipated elements to remain on track with these scenarios and to meet the desired objectives. Energy is recognized as a crucial component for every country's economic development. Energy is one of the main forces behind economic progress in India, a growing nation. According to the review, socioeconomic factors like GNP, energy prices, and population are all related to energy usage. The impact of socioeconomic factors on energy consumption is examined in this article using econometric models. The R2, SE, test is used to discover the best fit and to identify the important factors affecting energy consumption. It has been shown that demand for coal is influenced by population and coal price, but demand for oil is influenced by GNP per capita. The GNP and power price both affect how much electricity is demanded. The projected demand for electricity, coal, oil, and natural gas in India from 2030 to 2031 results in a total energy need of 22.944 1015 kJ.
Keywords
Energy Consumption, India, Prediction, Renewable, Machine Learning
