Artificial Intelligence and Machine Learning for Energy Consumption and Production in Emerging Markets

The energy industry is facing a broad variety of challenges all around the world, some of which include a rise in consumption as well as efficiency, shifting trends in both demand and supply, and a lack of the necessary analytics for effective management. These issues present themselves more extremely in countries that have emerging markets. Because there are several unauthorized connections to the electricity grid, a large amount of energy is not being measured or paid for. This is because there are numerous connections. Users are less likely to utilize energy efficiency when it is free, which leads to energy losses as well as greater CO2 emissions as a result of this. Energy losses also occur from the fact that this leads to higher CO2 emissions. The energy sector of industrialized nations has already begun to use artificial intelligence and other similar technologies to facilitate data sharing and coordination across smart grids, smart meters, and Internet of Things devices. These advancements have been made possible by the use of artificial intelligence. This is something that can be said about smart grids as well as smart meters. The purpose of this research was to evaluate the possible contributions that AI and ML technologies could make to the growth of energy production in developing countries. The primary focus of this research is on the problems that are brought about by the widespread lack of access to electricity and the frequent power cuts that are experienced in a great number of developing countries. A discussion on how AI and ML might be of aid to the energy sector in a range of emerging economies was the focus of the study. The conclusion consisted of a debate about what should be done for emerging countries to more significantly profit from the application of AI and ML in the energy sector.