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Energy demand is increasing globally due to the growing human population and progressive lifestyle. The adequate use of available energy resources, including renewable, contributes to a country&#x2019;s economic sustainability and future development. Optimization&#x2013;based energy management and cost minimization plays a significant role in overcoming energy crises in less developed countries. In this paper, an optimization&#x2013;based dynamic energy management technique for smart grids is developed based on the integration of available renewable resources and variable consumer demand, distinctive to underdeveloped countries. Consumer demand is classified into fixed, flexible, and highly variable based on population characteristics. In this work, we developed a Dynamic Multiple Knapsack DMKNS algorithm, which automatically schedules energy provision to various users by optimally accounting for the available resources (Grid and Renewable). The proposed method provides a low-cost solution by maintaining a constant energy supply while preserving consumer comfort and grid stability. The simulation results with various intermittent availability of resources using MKNS show a saving up to 50% for a variable energy demand user. The proposed method is general and can also be applied to various underdeveloped regions with similar consumer demand and statistics.

Efficient Energy Management for Household: Optimization-Based Integration of Distributed Energy Resources in Smart Grid