This paper presents a review of residential demand-side management (DSM) focusing on modeling approaches, optimization techniques, and future perspectives. Deterministic, stochastic, and data-driven models are analyzed to capture residential load behavior. Various optimization methods, including classical and artificial intelligence-based techniques, are discussed for improving energy efficiency and reducing peak demand. The role of smart grid technologies and IoT in enabling DSM is also examined. Key challenges and future research directions are highlighted.
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