Implementation of real-time optimal load scheduling for IoT-based intelligent smart energy management system using new decisive algorithm
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2025-03-15
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Springer Nature
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2314-7172
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This paper presents the implementation of a real-time optimal load scheduling system for an IoT-based intelligent smart energy management system (SEMS) using a novel decisive algorithm. The increasing use of electrical equipment by consumers often leads to a mismatch between demand and supply, posing signifcant challenges to the energy sector. The proposed system addresses these challenges by optimizing load distribution and enhancing energy efciency through advanced demand-side management techniques. By leveraging real-time data from IoT sensors and incorporating user preferences, the new algorithm dynamically adjusts power consumption to avoid peak-hour overloads, thus preventing widespread power outages. Experimental results demonstrate that the system efectively reduces overall energy consumption while maintaining user comfort and optimizing costs. The innovative approach of controlled partial load shedding based on consumer priorities ensures a balanced and resilient energy supply. This study highlights the potential of IoT and advanced algorithms in transforming energy management practices and providing sustainable solutions for the future.
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Citación
Journal of Electrical Systems and Inf Technol, Vol. 12, N° 6 (2025) p. 1-21.
Palabras clave
Demand response, Renewable energy, Internet of things, Sensor, Smart energy management systems, Smart plug, Smart grid
Licencia
Atribución-NoComercial-CompartirIgual 3.0 Chile (CC BY-NC-SA 3.0 CL)