HEMS using Machine Learning and IoT in Energy Management

Abstract

The smart grid is a significant component of our modern networks and society. Smart metres are essential. A smart metre offers user engagement, automated information gathering, energy control, and instantaneous monitoring of dependable status. Additionally, it offers two ways for information to move between suppliers and customers, improving efficiency and control. In addition, it offers power management and real-time usage information. As long as the customer’s maximum load demand exceeds the maximum Value, the electricity supply to customers will be separated with the help of implementation of IOT based system for HEMS. In an ideal environment with normal workload conditions, the smart meter has a service life of 5 to 6 years. In this paper the use of the smart meter with IOT Technology is introduced. Many methods are recommended, such as the Energy Monitoring and Prediction System, which is an effective way to keep an eye on the gadgets that are used in homes or businesses. In this research, we have focused on estimating the electric energy consumption of household appliances in a low-energy consumption flat using a machine learning technique. In order to enable demand-side management and allow any legitimate consumer to view their individual consumption rate remotely, this paper focused on a smart system that wirelessly profiles energy consumption by calculating the facility consumed by each individual consumer. The calculated rate is then transmitted to a cloud web server.