Smart Energy Management System Of Using Machine Learning

Abstract

Smart Energy Management Systems (SEMS) are an essential methods of addressing the global issue of inefficient energy usage. This paper provides a solution by proposing the use of machine learning (ML) approaches in the growth of a smart energy system. The system uses features such as request forecasting, optimization control, and business continuity planning support to optimize energy consumption and level out energy consumption fluctuations. The proposed system is powered by the advance technologies, such as the Internet of Things (IoT), Artificial Intelligence (AI), and ML. The system uses ML to provide accurate energy estimation for both hourly and day-ahead planning. Tests have shown that the proposed energy management system is able to achieve an accuracy rate of 90.1% and a miss rate of 9.9%. This system is a great way to ensure efficient energy usage, leading to financial savings, better sustainability, and improved quality of life. With its capabilities, the SEMS is a reliable and effective way to manage energy in an ever-changing environment.