The exploitation of Renewable Energy Sources within household is becoming essential to reduce energy bills and carbon footprint. To maximize its usage and benefit, smart devices, such as Smart Home Energy Management Systems, are essential to control the supply of domestic demand. In this study, different control strategies for an HEMS, with increasing complexity, have been compared. Results show that, even if simple control strategy are easy to be implemented, more complex algorithms with energy forecasting may perform better.

Control Strategies for Home Energy Management Systems / Leva, Sonia; Giacomelli, Gianluca; Magri, Chiara; Piccoli, Gianluca; Pierini, Matteo; Lazzeroni, Paolo; Cuccovillo, Andrea; Tosarello, Martina; Rosso, Marta; Lupo, Vinicio. - (2024), pp. 1-6. (Intervento presentato al convegno IEEE International Conference on Artificial Intelligence & Green Energy (ICAIGE) tenutosi a Yasmine Hammamet (TUN) nel 10-12 Ottobre 2024) [10.1109/icaige62696.2024.10776666].

Control Strategies for Home Energy Management Systems

Lazzeroni, Paolo;Cuccovillo, Andrea;Tosarello, Martina;
2024

Abstract

The exploitation of Renewable Energy Sources within household is becoming essential to reduce energy bills and carbon footprint. To maximize its usage and benefit, smart devices, such as Smart Home Energy Management Systems, are essential to control the supply of domestic demand. In this study, different control strategies for an HEMS, with increasing complexity, have been compared. Results show that, even if simple control strategy are easy to be implemented, more complex algorithms with energy forecasting may perform better.
2024
979-8-3503-8983-8
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2996164