Electric Water Boiler Energy Prediction: State-of-the-Art Review of Influencing Factors, Techniques, and Future Directions

Ibrahim Ali Kachalla and Christian Ghiaus ()
Additional contact information
Ibrahim Ali Kachalla: CETHIL UMR 5008, INSA Lyon, Université de Lyon, F-69621 Villeurbanne, France
Christian Ghiaus: CETHIL UMR 5008, INSA Lyon, Université de Lyon, F-69621 Villeurbanne, France

Energies, 2024, vol. 17, issue 2, 1-32

Abstract: Accurate and efficient prediction of electric water boiler (EWB) energy consumption is significant for energy management, effective demand response, cost minimisation, and robust control strategies. Adequate tracking and prediction of user behaviour can enhance renewable energy mini-grid (REMD) management. Fulfilling these demands for predicting the energy consumption of electric water boilers (EWB) would facilitate the establishment of a new framework that can enhance precise predictions of energy consumption trends for energy efficiency and demand management, which necessitates this state-of-the-art review. This article first reviews the factors influencing the prediction of energy consumption of electric water boilers (EWB); subsequently, it conducts a critical review of the current approaches and methods for predicting electric water boiler (EWB) energy consumption for residential building applications; after that, the performance evaluation methods are discussed. Finally, research gaps are ascertained, and recommendations for future work are summarised.

Keywords: daily energy consumption; electrical water boilers (EWB); prediction model; residential 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: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/17/2/443/pdf (application/pdf)
https://www.mdpi.com/1996-1073/17/2/443/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:17:y:2024:i:2:p:443-:d:1320347

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().