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This research presents an innovative approach to energy management in smart homes, aiming to efficiently regulate energy demands while ensuring customer loyalty. The focus is on addressing the limitations of existing demand-side management (DSM) programs, which predominantly target the residential sector. The proposed solution introduces the Adaptive Coati Optimization algorithm, which optimizes device organization based on Critical-Peak-Price and Real-Time-Price power payment systems. By strategically managing energy consumption, the algorithm reduces electrical expenses and peaks without compromising user convenience. The study evaluates the effectiveness of the approach across three operational periods (60 minutes, 12 minutes, and 24 minutes) to align with varying customer needs. Overall, the Adaptive Coati Optimization algorithm offers a promising solution for cost-efficient energy management in smart homes, combining both financial benefits and enhanced user satisfaction. The results indicate a significant decrease in tariffs rates, up to 30%, leading to a 20% increase in user satisfaction and a 25% improvement in cost utilization.
Balavignesh et al. (Fri,) studied this question.