Classification of Special Days in Short-Term Load Forecasting: The Spanish Case Study
Short-Term Load Forecasting is a very relevant aspect in managing, operating or participating an electric system. From system operators to energy producers and retailers knowing the electric demand in advance with high accuracy is a key feature for their business. The load series of a given system p...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-04-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/12/7/1253 |
| _version_ | 1811300936913518592 |
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| author | Miguel López Carlos Sans Sergio Valero Carolina Senabre |
| author_facet | Miguel López Carlos Sans Sergio Valero Carolina Senabre |
| author_sort | Miguel López |
| collection | DOAJ |
| description | Short-Term Load Forecasting is a very relevant aspect in managing, operating or participating an electric system. From system operators to energy producers and retailers knowing the electric demand in advance with high accuracy is a key feature for their business. The load series of a given system presents highly repetitive daily, weekly and yearly patterns. However, other factors like temperature or social events cause abnormalities in this otherwise periodic behavior. In order to develop an effective load forecasting system, it is necessary to understand and model these abnormalities because, in many cases, the higher forecasting error typical of these special days is linked to the larger part of the losses related to load forecasting. This paper focuses on the effect that several types of special days have on the load curve and how important it is to model these behaviors in detail. The paper analyzes the Spanish national system and it uses linear regression to model the effect that social events like holidays or festive periods have on the load curve. The results presented in this paper show that a large classification of events is needed in order to accurately model all the events that may occur in a 7-year period. |
| first_indexed | 2024-04-13T06:59:50Z |
| format | Article |
| id | doaj.art-7af4f9b8a1894813b16354d3d2d2119c |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-13T06:59:50Z |
| publishDate | 2019-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-7af4f9b8a1894813b16354d3d2d2119c2022-12-22T02:57:09ZengMDPI AGEnergies1996-10732019-04-01127125310.3390/en12071253en12071253Classification of Special Days in Short-Term Load Forecasting: The Spanish Case StudyMiguel López0Carlos Sans1Sergio Valero2Carolina Senabre3Electrical Engineering Area, University Miguel Hernández, Av. de la Universidad, s/n, 03202 Elche, SpainElectrical Engineering Area, University Miguel Hernández, Av. de la Universidad, s/n, 03202 Elche, SpainElectrical Engineering Area, University Miguel Hernández, Av. de la Universidad, s/n, 03202 Elche, SpainElectrical Engineering Area, University Miguel Hernández, Av. de la Universidad, s/n, 03202 Elche, SpainShort-Term Load Forecasting is a very relevant aspect in managing, operating or participating an electric system. From system operators to energy producers and retailers knowing the electric demand in advance with high accuracy is a key feature for their business. The load series of a given system presents highly repetitive daily, weekly and yearly patterns. However, other factors like temperature or social events cause abnormalities in this otherwise periodic behavior. In order to develop an effective load forecasting system, it is necessary to understand and model these abnormalities because, in many cases, the higher forecasting error typical of these special days is linked to the larger part of the losses related to load forecasting. This paper focuses on the effect that several types of special days have on the load curve and how important it is to model these behaviors in detail. The paper analyzes the Spanish national system and it uses linear regression to model the effect that social events like holidays or festive periods have on the load curve. The results presented in this paper show that a large classification of events is needed in order to accurately model all the events that may occur in a 7-year period.https://www.mdpi.com/1996-1073/12/7/1253load forecastingspecial daysregressive models |
| spellingShingle | Miguel López Carlos Sans Sergio Valero Carolina Senabre Classification of Special Days in Short-Term Load Forecasting: The Spanish Case Study Energies load forecasting special days regressive models |
| title | Classification of Special Days in Short-Term Load Forecasting: The Spanish Case Study |
| title_full | Classification of Special Days in Short-Term Load Forecasting: The Spanish Case Study |
| title_fullStr | Classification of Special Days in Short-Term Load Forecasting: The Spanish Case Study |
| title_full_unstemmed | Classification of Special Days in Short-Term Load Forecasting: The Spanish Case Study |
| title_short | Classification of Special Days in Short-Term Load Forecasting: The Spanish Case Study |
| title_sort | classification of special days in short term load forecasting the spanish case study |
| topic | load forecasting special days regressive models |
| url | https://www.mdpi.com/1996-1073/12/7/1253 |
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