Proceedings of the 2nd International Conference on Industry 4.0 and Artificial Intelligence (ICIAI 2021)

Home Energy Management Machine Learning Prediction Algorithms: A Review

Authors
Ohoud Almughram1, *, Bassam Zafar2, Sami Ben Slama3
1,2Information Systems Department, FCIT, King Abdulaziz University, Jeddah, Saudi Arabia
3Faculty of Applied Studies, King Abdulaziz University, Jeddah, Saudi Arabia
Corresponding Author
Ohoud Almughram
Available Online 2 February 2022.
DOI
10.2991/aisr.k.220201.008How to use a DOI?
Keywords
Home Energy Management System; Machine Learning algorithm; Prediction; Forecasting; Optimization
Abstract

Renewable energies are being introduced in countries around the world to move away from the environmental impacts from fossil fuels. In the residential sector, smart buildings that utilize smart appliances, integrate information and communication technology and utilize a renewable energy source for in-house power generation are becoming popular. Accordingly, there is a need to understand what factors influence the accuracy of managing such smart buildings. Thus, this study reviews the application of machine learning prediction algorithms in Home Energy Management Systems. Various aspects are covered, such as load forecasting, household consumption prediction, rooftop solar energy generation, and price prediction. Also, a proposed Home Energy Management System framework is included based on the most accurate machine learning prediction algorithms of previous studies. This review supports research into the selection of an appropriate model for predicting energy consumption of smart buildings.

Copyright
© 2022 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

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Volume Title
Proceedings of the 2nd International Conference on Industry 4.0 and Artificial Intelligence (ICIAI 2021)
Series
Advances in Intelligent Systems Research
Publication Date
2 February 2022
ISBN
978-94-6239-528-2
ISSN
1951-6851
DOI
10.2991/aisr.k.220201.008How to use a DOI?
Copyright
© 2022 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Ohoud Almughram
AU  - Bassam Zafar
AU  - Sami Ben Slama
PY  - 2022
DA  - 2022/02/02
TI  - Home Energy Management Machine Learning Prediction Algorithms: A Review
BT  - Proceedings of the 2nd International Conference on Industry 4.0 and Artificial Intelligence (ICIAI 2021)
PB  - Atlantis Press
SP  - 40
EP  - 47
SN  - 1951-6851
UR  - https://doi.org/10.2991/aisr.k.220201.008
DO  - 10.2991/aisr.k.220201.008
ID  - Almughram2022
ER  -