Cover Image

Electrical Load Forecasting Models for Different Generation Modalities: A Review

The intelligent management of power in electrical utilities depends on the high significance of load forecasting models. Since the industries are digitalized, power generation is supported by a variety of resources. Therefore, the forecasting accuracy of different models varies. The power utilities...

Full description

Saved in:
Bibliographic Details
Main Authors: Azeem, A., Ismail, I., Jameel, S.M., Harindran, V.R.
Format: Article
Published: Institute of Electrical and Electronics Engineers Inc. 2021
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117783837&doi=10.1109%2fACCESS.2021.3120731&partnerID=40&md5=c4df37d4a6577baf7556289a7596ae01
http://eprints.utp.edu.my/29397/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utp.eprints.29397
record_format eprints
spelling my.utp.eprints.293972022-03-25T01:50:28Z Electrical Load Forecasting Models for Different Generation Modalities: A Review Azeem, A. Ismail, I. Jameel, S.M. Harindran, V.R. The intelligent management of power in electrical utilities depends on the high significance of load forecasting models. Since the industries are digitalized, power generation is supported by a variety of resources. Therefore, the forecasting accuracy of different models varies. The power utilities with different generation modalities (DGM) experience complexities and a noticeable amount of error in predicting future electrical consumption. To effectively manage the power flow with negligible power interruptions, a utility must utilize the forecasting tools to predict the future electricity demand with minimum error. Since the current literature supports individual and limited power sources involved in generation for load forecasting, thus the utilities with multiple power sources or DGM remain unexplored. Therefore, exploration of existing literature is required relating to analyzing the existing models which could be considered in load forecasting for DGM. This paper explores state-of-art methods recently utilized for electrical load forecasting highlighting the common practices, recent advances, and exposure of areas available for improvement. The review investigates the methods, parameters, and respective sectors considered for load forecasting. It performs in-depth analysis and discusses the strengths, weaknesses, and error percentages of models. It also highlights the peculiarities of methods used in residential, commercial, industrial, grid, and off-grid sectors aiming to help the researchers to appraise the common practices. Moreover, trends and research gaps are also discussed. © 2013 IEEE. Institute of Electrical and Electronics Engineers Inc. 2021 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117783837&doi=10.1109%2fACCESS.2021.3120731&partnerID=40&md5=c4df37d4a6577baf7556289a7596ae01 Azeem, A. and Ismail, I. and Jameel, S.M. and Harindran, V.R. (2021) Electrical Load Forecasting Models for Different Generation Modalities: A Review. IEEE Access, 9 . pp. 142239-142263. http://eprints.utp.edu.my/29397/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description The intelligent management of power in electrical utilities depends on the high significance of load forecasting models. Since the industries are digitalized, power generation is supported by a variety of resources. Therefore, the forecasting accuracy of different models varies. The power utilities with different generation modalities (DGM) experience complexities and a noticeable amount of error in predicting future electrical consumption. To effectively manage the power flow with negligible power interruptions, a utility must utilize the forecasting tools to predict the future electricity demand with minimum error. Since the current literature supports individual and limited power sources involved in generation for load forecasting, thus the utilities with multiple power sources or DGM remain unexplored. Therefore, exploration of existing literature is required relating to analyzing the existing models which could be considered in load forecasting for DGM. This paper explores state-of-art methods recently utilized for electrical load forecasting highlighting the common practices, recent advances, and exposure of areas available for improvement. The review investigates the methods, parameters, and respective sectors considered for load forecasting. It performs in-depth analysis and discusses the strengths, weaknesses, and error percentages of models. It also highlights the peculiarities of methods used in residential, commercial, industrial, grid, and off-grid sectors aiming to help the researchers to appraise the common practices. Moreover, trends and research gaps are also discussed. © 2013 IEEE.
format Article
author Azeem, A.
Ismail, I.
Jameel, S.M.
Harindran, V.R.
spellingShingle Azeem, A.
Ismail, I.
Jameel, S.M.
Harindran, V.R.
Electrical Load Forecasting Models for Different Generation Modalities: A Review
author_facet Azeem, A.
Ismail, I.
Jameel, S.M.
Harindran, V.R.
author_sort Azeem, A.
title Electrical Load Forecasting Models for Different Generation Modalities: A Review
title_short Electrical Load Forecasting Models for Different Generation Modalities: A Review
title_full Electrical Load Forecasting Models for Different Generation Modalities: A Review
title_fullStr Electrical Load Forecasting Models for Different Generation Modalities: A Review
title_full_unstemmed Electrical Load Forecasting Models for Different Generation Modalities: A Review
title_sort electrical load forecasting models for different generation modalities: a review
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2021
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117783837&doi=10.1109%2fACCESS.2021.3120731&partnerID=40&md5=c4df37d4a6577baf7556289a7596ae01
http://eprints.utp.edu.my/29397/
_version_ 1738656960140541952
score 13.211869

Similar Items