Methods and Models for Electric Load Forecasting: A Comprehensive Review
Electric load forecasting (ELF) is a vital process in the planning of the electricity industry and plays a crucial role in electric capacity scheduling and power systems management and, therefore, it has attracted increasing academic interest. Hence, the accuracy of electric load forecasting has gre...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2020-02-01
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| Series: | Logistics & Sustainable Transport |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/jlst-2020-0004 |
| _version_ | 1797963499763138560 |
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| author | Hammad Mahmoud A. Jereb Borut Rosi Bojan Dragan Dejan |
| author_facet | Hammad Mahmoud A. Jereb Borut Rosi Bojan Dragan Dejan |
| author_sort | Hammad Mahmoud A. |
| collection | DOAJ |
| description | Electric load forecasting (ELF) is a vital process in the planning of the electricity industry and plays a crucial role in electric capacity scheduling and power systems management and, therefore, it has attracted increasing academic interest. Hence, the accuracy of electric load forecasting has great importance for energy generating capacity scheduling and power system management. This paper presents a review of forecasting methods and models for electricity load. About 45 academic papers have been used for the comparison based on specified criteria such as time frame, inputs, outputs, the scale of the project, and value. The review reveals that despite the relative simplicity of all reviewed models, the regression analysis is still widely used and efficient for long-term forecasting. As for short-term predictions, machine learning or artificial intelligence-based models such as Artificial Neural Networks (ANN), Support Vector Machines (SVM), and Fuzzy logic are favored. |
| first_indexed | 2024-04-11T01:30:26Z |
| format | Article |
| id | doaj.art-6d64c46c85f241c6a8e5466a9f8714c3 |
| institution | Directory Open Access Journal |
| issn | 2232-4968 |
| language | English |
| last_indexed | 2024-04-11T01:30:26Z |
| publishDate | 2020-02-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Logistics & Sustainable Transport |
| spelling | doaj.art-6d64c46c85f241c6a8e5466a9f8714c32023-01-03T09:55:06ZengSciendoLogistics & Sustainable Transport2232-49682020-02-01111517610.2478/jlst-2020-0004jlst-2020-0004Methods and Models for Electric Load Forecasting: A Comprehensive ReviewHammad Mahmoud A.0Jereb Borut1Rosi Bojan2Dragan Dejan3Arab Academy for Science, Technology and Maritime Transport,Alexandria, EgyptUniversity of Maribor/Faculty of Logistics, Celje, SloveniaUniversity of Maribor/Faculty of Logistics, Celje, SloveniaUniversity of Maribor/Faculty of Logistics, Celje, SloveniaElectric load forecasting (ELF) is a vital process in the planning of the electricity industry and plays a crucial role in electric capacity scheduling and power systems management and, therefore, it has attracted increasing academic interest. Hence, the accuracy of electric load forecasting has great importance for energy generating capacity scheduling and power system management. This paper presents a review of forecasting methods and models for electricity load. About 45 academic papers have been used for the comparison based on specified criteria such as time frame, inputs, outputs, the scale of the project, and value. The review reveals that despite the relative simplicity of all reviewed models, the regression analysis is still widely used and efficient for long-term forecasting. As for short-term predictions, machine learning or artificial intelligence-based models such as Artificial Neural Networks (ANN), Support Vector Machines (SVM), and Fuzzy logic are favored.https://doi.org/10.2478/jlst-2020-0004electric load forecastingmodeling electricity loadsmethods and models of forecasting |
| spellingShingle | Hammad Mahmoud A. Jereb Borut Rosi Bojan Dragan Dejan Methods and Models for Electric Load Forecasting: A Comprehensive Review Logistics & Sustainable Transport electric load forecasting modeling electricity loads methods and models of forecasting |
| title | Methods and Models for Electric Load Forecasting: A Comprehensive Review |
| title_full | Methods and Models for Electric Load Forecasting: A Comprehensive Review |
| title_fullStr | Methods and Models for Electric Load Forecasting: A Comprehensive Review |
| title_full_unstemmed | Methods and Models for Electric Load Forecasting: A Comprehensive Review |
| title_short | Methods and Models for Electric Load Forecasting: A Comprehensive Review |
| title_sort | methods and models for electric load forecasting a comprehensive review |
| topic | electric load forecasting modeling electricity loads methods and models of forecasting |
| url | https://doi.org/10.2478/jlst-2020-0004 |
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