Assessing energy forecasting inaccuracy by simultaneously considering temporal and absolute errors
| dc.contributor.author | Frías Paredes, Laura | |
| dc.contributor.author | Mallor Giménez, Fermín | |
| dc.contributor.author | Gastón Romeo, Martín | |
| dc.contributor.author | León, Teresa | |
| dc.contributor.department | Estadística e Investigación Operativa | es_ES |
| dc.contributor.department | Estatistika eta Ikerketa Operatiboa | eu |
| dc.contributor.department | Institute of Smart Cities - ISC | en |
| dc.date.accessioned | 2024-11-18T11:05:12Z | |
| dc.date.available | 2024-11-18T11:05:12Z | |
| dc.date.issued | 2017-04-17 | |
| dc.date.updated | 2024-11-18T10:58:31Z | |
| dc.description.abstract | Recent years have seen a growing trend in wind and solar energy generation globally and it is expected that an important percentage of total energy production comes from these energy sources. However, they present inherent variability that implies uctuations in energy generation that are dicult to forecast. Thus, forecasting errors have a considerable role in the impacts and costs of renewable energy integration, management, and commercialization. This study presents an important advance in the task of analyzing prediction models, in particular, in the timing component of prediction error, which improves previous pioneering results. A new method to match time series is dened in order to assess energy forecasting accuracy. This method relies on a new family of step patterns, an essential component of the algorithm to evaluate the temporal distortion index (TDI). This family minimizes the mean absolute error (MAE) of the transformation with respect to the reference series (the real energy series) and also allows detailed control of the temporal distortion entailed in the prediction series. The simultaneous consideration of temporal and absolute errors allows the use of Pareto frontiers as characteristic error curves. Real examples of wind energy forecasts are used to illustrate the results. | en |
| dc.description.sponsorship | This paper has been supported under Grants MTM 2012-36025 and DPI 2013-47279-C2-1-R. The authors are grateful to the research staff of the National Renewable Energy Center of Spain (CENER) for their help in the development of this new methodology of error analysis through the contribution of their prediction model LocalPred. | |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Frías-Paredes, L., Mallor-Giménez, F., Gastón-Romeo, M., León, T. (2017). Assessing energy forecasting inaccuracy by simultaneously considering temporal and absolute errors. Energy Conversion and Management, 142, 533-546. https://doi.org/10.1016/j.enconman.2017.03.056. | |
| dc.identifier.doi | 10.1016/j.enconman.2017.03.056 | |
| dc.identifier.issn | 0196-8904 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/52524 | |
| dc.language.iso | eng | |
| dc.publisher | Elsevier | |
| dc.relation.ispartof | Energy Conversion and Management (2017), vol. 142 | |
| dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//DPI2013-47279-C2-1-R/ES/ | |
| dc.relation.publisherversion | https://doi.org/10.1016/j.enconman.2017.03.056 | |
| dc.rights | © 2017 Elsevier Ltd. This manuscript version is made available under the CC-BY-NC-ND 4.0 | |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Energy forecasting accuracy | en |
| dc.subject | Temporal misalignment | en |
| dc.subject | Renewable | en |
| dc.title | Assessing energy forecasting inaccuracy by simultaneously considering temporal and absolute errors | en |
| dc.type | info:eu-repo/semantics/article | |
| dc.type.version | info:eu-repo/semantics/acceptedVersion | |
| dspace.entity.type | Publication | |
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