An IoT Enabled Energy Management System with Precise Forecasting and Load Optimization for PV Power Generation

The challenge of demand-side energy management involves effectively leveraging renewable energy sources while mitigating power consumption constraints. The Intelligent Smart Energy Management System (ISEMS) aims to address this by accurately estimating energy availability and planning ahead for optimal usage. ISEMS utilizes Support Vector Machine (SVM) regression model with Particle Swarm Optimization (PSO) to forecast energy with high precision. Evaluation against other models demonstrates superior accuracy. Experimental setup of ISEMS is presented, showcasing its performance across different configurations, prioritizing user comfort. Additionally, integration of Internet of Things (IoT) enables user-end monitoring.