Assessing Tolerance-Based Robust Short-Term Load Forecasting in Buildings
Short-term load forecasting (STLF) in buildings differs from its broader counterpart in that the load to be predicted does not seem to be stationary, seasonal and regular but, on the contrary, it may be subject to sudden changes and variations on its consumption behaviour. Classical STLF methods do...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2013-04-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1996-1073/6/4/2110 |
| _version_ | 1798006756675158016 |
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| author | Juan Prieto Oscar Bretos Iván Fernández Yoseba K. Penya Cruz E. Borges |
| author_facet | Juan Prieto Oscar Bretos Iván Fernández Yoseba K. Penya Cruz E. Borges |
| author_sort | Juan Prieto |
| collection | DOAJ |
| description | Short-term load forecasting (STLF) in buildings differs from its broader counterpart in that the load to be predicted does not seem to be stationary, seasonal and regular but, on the contrary, it may be subject to sudden changes and variations on its consumption behaviour. Classical STLF methods do not react fast enough to these perturbations (i.e., they are not robust) and the literature on building STLF has not yet explored this area. Hereby, we evaluate a well-known post-processing method (Learning Window Reinitialization) applied to two broadly-used STLF algorithms (Autoregressive Model and Support Vector Machines) in buildings to check their adaptability and robustness. We have tested the proposed method with real-world data and our results state that this methodology is especially suited for buildings with non-regular consumption profiles, as classical STLF methods are enough to model regular-profiled ones. |
| first_indexed | 2024-04-11T12:59:41Z |
| format | Article |
| id | doaj.art-a59301c4d7e243299cbd002191cbe16f |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T12:59:41Z |
| publishDate | 2013-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-a59301c4d7e243299cbd002191cbe16f2022-12-22T04:22:59ZengMDPI AGEnergies1996-10732013-04-01642110212910.3390/en6042110Assessing Tolerance-Based Robust Short-Term Load Forecasting in BuildingsJuan PrietoOscar BretosIván FernándezYoseba K. PenyaCruz E. BorgesShort-term load forecasting (STLF) in buildings differs from its broader counterpart in that the load to be predicted does not seem to be stationary, seasonal and regular but, on the contrary, it may be subject to sudden changes and variations on its consumption behaviour. Classical STLF methods do not react fast enough to these perturbations (i.e., they are not robust) and the literature on building STLF has not yet explored this area. Hereby, we evaluate a well-known post-processing method (Learning Window Reinitialization) applied to two broadly-used STLF algorithms (Autoregressive Model and Support Vector Machines) in buildings to check their adaptability and robustness. We have tested the proposed method with real-world data and our results state that this methodology is especially suited for buildings with non-regular consumption profiles, as classical STLF methods are enough to model regular-profiled ones.http://www.mdpi.com/1996-1073/6/4/2110short term load forecastingartificial intelligencestatistical methods |
| spellingShingle | Juan Prieto Oscar Bretos Iván Fernández Yoseba K. Penya Cruz E. Borges Assessing Tolerance-Based Robust Short-Term Load Forecasting in Buildings Energies short term load forecasting artificial intelligence statistical methods |
| title | Assessing Tolerance-Based Robust Short-Term Load Forecasting in Buildings |
| title_full | Assessing Tolerance-Based Robust Short-Term Load Forecasting in Buildings |
| title_fullStr | Assessing Tolerance-Based Robust Short-Term Load Forecasting in Buildings |
| title_full_unstemmed | Assessing Tolerance-Based Robust Short-Term Load Forecasting in Buildings |
| title_short | Assessing Tolerance-Based Robust Short-Term Load Forecasting in Buildings |
| title_sort | assessing tolerance based robust short term load forecasting in buildings |
| topic | short term load forecasting artificial intelligence statistical methods |
| url | http://www.mdpi.com/1996-1073/6/4/2110 |
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