Optimizing home energy systems through algorithmic techniques

The growing demand for sustainable energy consumption, coupled with the rapid adoption of smart home technologies, has elevated the importance of optimizing residential energy systems. This paper provides a comprehensive survey of algorithmic techniques applied to home energy optimization, examining their underlying principles, strengths, limitations, and areas of applicability. The surveyed approaches are categorized into rule-based methods, optimization-driven models, artificial intelligence (AI)-based strategies, and hybrid frameworks. By analyzing their effectiveness across diverse residential energy management scenarios, the study aims to present a structured overview of the state-of-the-art while highlighting emerging challenges and potential directions for future research in intelligent home energy optimization.