IoT residential appliance monitoring and controlling system using MQTT protocol Available to Purchase

The rising energy demand for the residential sector is a new opportunity for load management to enhance energy consumption, especially during peak load periods. In the smart grid, peak demand periods have a significant impact on energy consumption. During peak periods, due to increasing demand, the utility company must increase its generation capacity. For this reason, the demand response of smart grids has helped to balance the required energy demand with the available generation resources, which lately gained widespread attention. The proposed system addresses the possibility of off-location control of household electrical appliances through the integration with the Internet of things (IoT) Monitoring and controlling energy use in a building is made easier by the use of building-energy monitoring systems. minimize power consumption to the barest minimum. The key feature of the proposed system is the ability to remotely monitor and manage electrical and electronic appliances to minimize peak load to the barest minimum. The plan has both efficiency and accuracy advantages, as well as financial advantages, Particle Swarm Optimization (PSO) is employed to optimize the load consumption of a typical residential building, and Home Energy Management Systems(HEMS) is an intelligent system that performs the functions of planning, monitoring, and controlling energy that is used inside a building. It is intended to offer a desirable demand response based on the system conditions and the price scheme by the utility. A smart plug helps a consumer remotely monitor and control the electrical appliances. Raspberry Pi has been used and programmed to become one of the main elements of the Energy Management Controller (EMC). It can send and receives commands to a smart plug using the Message Queuing Telemetry Transport (MQTT) protocol according to the optimal scheduling time of household appliances, to add to that, show in this paper demonstrates is that how the device may be accessed and controlled to reduce energy use in the home, as well as a 24.31 percent reduction in the cost of energy consumption. based on the optimization method modeling.