Design of Ensemble Forecasting Models for Home Energy Management Systems

Karol Bot, Samira Santos, Inoussa Laouali, Antonio Ruano and Maria da Graça Ruano
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Karol Bot: Faculty of Science & Technology, University of Algarve, 8005-294 Faro, Portugal
Samira Santos: Faculty of Science & Technology, University of Algarve, 8005-294 Faro, Portugal
Inoussa Laouali: Faculty of Science & Technology, University of Algarve, 8005-294 Faro, Portugal
Antonio Ruano: Faculty of Science & Technology, University of Algarve, 8005-294 Faro, Portugal
Maria da Graça Ruano: Faculty of Science & Technology, University of Algarve, 8005-294 Faro, Portugal

Energies, 2021, vol. 14, issue 22, 1-37

Abstract: The increasing levels of energy consumption worldwide is raising issues with respect to surpassing supply limits, causing severe effects on the environment, and the exhaustion of energy resources. Buildings are one of the most relevant sectors in terms of energy consumption; as such, efficient Home or Building Management Systems are an important topic of research. This study discusses the use of ensemble techniques in order to improve the performance of artificial neural networks models used for energy forecasting in residential houses. The case study is a residential house, located in Portugal, that is equipped with PV generation and battery storage and controlled by a Home Energy Management System (HEMS). It has been shown that the ensemble forecasting results are superior to single selected models, which were already excellent. A simple procedure was proposed for selecting the models to be used in the ensemble, together with a heuristic to determine the number of models.

Keywords: energy systems; machine learning; forecasting; energy management systems; multi-objective genetic algorithms; ensemble models; energy in buildings (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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