Optimization Strategies in Residential Energy Management Systems: A Comprehensive Review

Abstract

The energy industry is undergoing a series of profound changes, leading to increased participation of consumers in grid operation. Prosumers, namely consumers who use energy and also produce it, are relying more on domestic renewable energy sources that offer environmental benefits but also impose new demands on the governance of these energies. A reliable energy supply in residential areas is an important issue; thus, poor management may cause interruptions and high operation costs. Home energy management systems (EMS) help consumers in overcoming these challenges by reducing energy usage for better cost savings while improving grid resiliency. This paper provides a complete study of the developmental techniques utilized at these systems, focusing on technical as well as computational aspects. The literature review is systematically classified into four categories: classical mathematical optimization, model predictive control (MPC), heuristics and metaheuristics, and other iterative control strategies. The period from 2019 to 2025 is examined, highlighting the need for clear ontology analysis due to the rapid growth of IoT-oriented EMSs, increased use of renewable generation, and the expansion of artificial intelligence (AI)–based solutions for optimization. The review highlights both current advancements and existing limitations in the field.