Energy Management System (EMS) is a major component of a smart grid and significant for the operational qualification. Controlling the residential grid, resulting into improving cost, emission, and comfort. The study aims to investigate the optimization methods used in Home Energy Management System(HEMS) and evaluate their effectiveness. The paper dis-cusses the architecture of HEMS, which is classified into three layers: physical, communication, and software. The physical layer comprises measurement systems and sensors for data acquisition, including smart meters, IoT sensors and smart appliances. The communication layer facilitates the interconnection between the control systems, central platforms, and smart devices. The software layer comprises the algorithmic and programming parts to optimize the system. Culminate into evaluating the different optimization methods used in HEMS, including mathematical, meta-heuristic, and artificial intelligence models.

An Overview of Optimization Methods for Home Energy Management Systems

Saleptsis M.;Mussetta M.;Leva S.
2024-01-01

Abstract

Energy Management System (EMS) is a major component of a smart grid and significant for the operational qualification. Controlling the residential grid, resulting into improving cost, emission, and comfort. The study aims to investigate the optimization methods used in Home Energy Management System(HEMS) and evaluate their effectiveness. The paper dis-cusses the architecture of HEMS, which is classified into three layers: physical, communication, and software. The physical layer comprises measurement systems and sensors for data acquisition, including smart meters, IoT sensors and smart appliances. The communication layer facilitates the interconnection between the control systems, central platforms, and smart devices. The software layer comprises the algorithmic and programming parts to optimize the system. Culminate into evaluating the different optimization methods used in HEMS, including mathematical, meta-heuristic, and artificial intelligence models.
2024
Proceedings - 24th EEEIC International Conference on Environment and Electrical Engineering and 8th I and CPS Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2024
Artificial Intelligence
Forecasting
Home Energy Management Systems
Optimization
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1281734
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