Home Energy Management System, Smart Load Management, Energy Efficiency, Energy Management Control, Internet of Things, Artificial Intelligence, Machine Learning, Grid Stability, Energy Storage, Smart Grids A Home Energy Management System (HEMS) is a key innovation in modern energy conservation, designed to optimize electricity usage by regulating residential loads. This paper introduces an Energy Management Control (EMC) system for Smart Homes (SH) that schedules household appliances efficiently, integrating Time of Use (TOU) and Inclining Block Rate (IBR) pricing models to manage demand within grid capacity. The Smart Load Management (SLM) system, supported by IoT, AI, and Machine Learning (ML), enhances real-time load balancing by predicting consumption patterns, integrating renewable energy sources, and responding dynamically to grid fluctuations. This study explores the latest advancements in SLM technology, evaluating its impact on energy efficiency, grid stability, and cost reduction. The paper also discusses future trends in energy storage and smart grids, emphasizing sustainability and resilience in power management.