<p>This paper presents a Systematic Literature Review (SLR) of Demand-Side Management (DSM) models in smart grids, covering research from 2018 to 2025 and following the PRISMA protocol. DSM models are essential for optimizing energy consumption, integrating renewable energy, and balancing grid loads; however, they face significant challenges in technical, economic, regulatory, and social domains. The review identifies key research gaps and explores emerging trends and strategic research directions. Our findings in results of bibliometric analysis using the Biblioshiny Tool reveal that optimization-based DSM models, such as Mixed-Integer Linear Programming (MILP) and robust optimization, are the most researched, while areas like machine learning applications and Blockchain-IoT integration remain underexplored, offering high potential for future innovation. To address these challenges, this paper proposes solutions focusing on four primary areas: enhancing technical infrastructure through advanced energy storage systems, implementing dynamic pricing models for improved economic viability, modernizing regulatory frameworks for market integration, and fostering consumer engagement through education and incentives. Additionally, the integration of machine learning-based forecasting and IoT-driven communication networks is emphasized to enhance model efficiency and responsiveness. By tackling these barriers, our proposed strategies aim to support the effective deployment of DSM programs, facilitating a sustainable and resilient energy system. The insights from this review are intended to guide researchers and policymakers in advancing DSM deployment, especially concerning consumer engagement and renewable energy integration within smart grids.</p>