Power allocation model for residential homes using AI-based IoT

Abstract

Conventional power transmission and distribution schemes have been completely transformed by the development of the Smart Grid (SG). Nearly every field has been impacted by technology and advancements, including smart grids. Electricity also isn't inexpensive to produce, so Smart Meters (SM) play a crucial role in controlling, managing, and performing efficiency to use the electricity successfully on the customer side, which would be referred to as demand side management (DSM). A Home Energy Management System (HEMS) has been proposed in the research study as a way of optimizing home appliances and saving as much money as possible. The Eagle Hard Optimization (EHO) method and our hybridization of the EHO technique have been implemented. EHO appears to be a Genetic Algorithm (GA) known as a Genetic EHO (GEHO). Compared to normal EHO and unplanned systems, simulation results showed that GEHO better planned the devices to lower the maximum price. Peak to Average Ration packs (PAR) has additionally been noted. Due to the planning of the largest amount of devices on both sides, GEHO& unforeseen has PAR equal, while EHO has a low PAR. Various Operation Time Intervals (OTI) were used to help in efficiency measures. With each of the three plans, capacity & costs money have indeed been thoroughly analyzed.

Keywords

• Smart grid
• Energy management system
• Genetic elephant herd optimization
• Cost optimization