Introducing the Temporal Distortion Index to perform a bidimensional analysis of renewable energy forecast
| dc.contributor.author | Frías Paredes, Laura | |
| dc.contributor.author | Mallor Giménez, Fermín | |
| dc.contributor.author | León, Teresa | |
| dc.contributor.author | Gastón Romeo, Martín | |
| 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 | 2024-11-18T11:23:15Z | |
| dc.date.available | 2024-11-18T11:23:15Z | |
| dc.date.issued | 2015-11-21 | |
| dc.date.updated | 2024-11-18T11:16:58Z | |
| dc.description.abstract | Wind has been the largest contributor to the growth of renewal energy during the early 21st century. However, the natural uncertainty that arises in assessing the wind resource implies the occurrence of wind power forecasting errors which perform a considerable role in the impacts and costs in the wind energy integration and its commercialization. The main goal of this paper is to provide a deeper insight in the analysis of timing errors which leads to the proposal of a new methodology for its control and measure. A new methodology, based on Dynamic TimeWarping, is proposed to be considered in the estimation of accuracy as attribute of forecast quality. A new dissimilarity measure, the Temporal Distortion Index, among time series is introduced to complement the traditional verication measures found in the literature. Furthermore we provide a bi-criteria perspective to the problem of comparing different forecasts. The methodology is illustrated with several examples including a real case. | |
| dc.description.sponsorship | This paper has been supported under Grants MTM 2012-36025 and DPI 490 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 analysis of errors contributing with their prediction model LocalPred. | |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Frías-Paredes, L., Mallor, F., León, T., Gastón-Romeo, M. (2015) Introducing the Temporal Distortion Index to perform a bidimensional analysis of renewable energy forecast. Energy, 94, 180-194. https://doi.org/10.1016/j.energy.2015.10.093 | |
| dc.identifier.doi | 10.1016/j.energy.2015.10.093 | |
| dc.identifier.issn | 0360-5442 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/52525 | |
| dc.language.iso | eng | |
| dc.publisher | Elsevier | |
| dc.relation.ispartof | Energy, 94(2016), 180-194 | |
| dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//MTM2012-36025/ES/ | |
| dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//DPI2013-47279-C2-1-R/ES/ | |
| dc.relation.publisherversion | https://doi.org/10.1016/j.energy.2015.10.093 | |
| dc.rights | © 2015 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 | Forecast accuracy | en |
| dc.subject | Temporal misalignment | en |
| dc.subject | Dynamic time warping | en |
| dc.subject | Renewable energy | en |
| dc.subject | Temporal Distortion Index | en |
| dc.subject | Bidimensional error | en |
| dc.title | Introducing the Temporal Distortion Index to perform a bidimensional analysis of renewable energy forecast | en |
| dc.type | info:eu-repo/semantics/article | |
| dc.type.version | info:eu-repo/semantics/acceptedVersion | |
| dspace.entity.type | Publication | |
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