Integrating long-term economic scenarios into peak load forecasting: An application to Spain
The treatment of trend components in electricity demand is critical for long-term peak load forecasting. When forecasting high frequency variables, like daily or hourly loads, a typical problem is how to make long-term scenarios - regarding demographics, GDP growth, etc. - compatible with short-term...
| Autores: | , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2017 |
| País: | España |
| Institución: | Universidad Autónoma de Madrid |
| Repositorio: | Biblos-e Archivo. Repositorio Institucional de la UAM |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.uam.es:10486/705760 |
| Acceso en línea: | http://hdl.handle.net/10486/705760 https://dx.doi.org/10.1016/j.energy.2017.08.113 |
| Access Level: | acceso abierto |
| Palabra clave: | Load curve forecasting Long-term scenarios Peak load forecasting Temporal disaggregation Economía |
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Integrating long-term economic scenarios into peak load forecasting: An application to SpainMoral Carcedo, JuliánPérez García, JuliánLoad curve forecastingLong-term scenariosPeak load forecastingTemporal disaggregationEconomíaThe treatment of trend components in electricity demand is critical for long-term peak load forecasting. When forecasting high frequency variables, like daily or hourly loads, a typical problem is how to make long-term scenarios - regarding demographics, GDP growth, etc. - compatible with short-term projections. Traditional procedures that apply de-trending methods are unable to simulate forecasts under alternative long-term scenarios. On the other hand, existing models that allow for changes in long-term trends tend to be characterized by end-of-year discontinuities. In this paper a novel forecasting procedure is presented that improves upon these approaches and is able to combine long and short-term features by employing temporal disaggregation techniques. This method is applied to forecast electricity load for Spain and its performance is compared to that of a nonlinear autoregressive neural network with exogenous inputs. Our proposed procedure is flexible enough to be applied to different scenarios based on alternative assumptions regarding both long-term trends as well as short-term projectionsElsevierDepartamento de Análisis Económico: Teoría Económica e Historia EconómicaDepartamento de Economía AplicadaFacultad de Ciencias Económicas y Empresariales20172017-08-30research articlehttp://purl.org/coar/resource_type/c_2df8fbb1AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10486/705760https://dx.doi.org/10.1016/j.energy.2017.08.113reponame:Biblos-e Archivo. Repositorio Institucional de la UAMinstname:Universidad Autónoma de MadridInglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:repositorio.uam.es:10486/7057602026-06-23T12:46:27Z |
| dc.title.none.fl_str_mv |
Integrating long-term economic scenarios into peak load forecasting: An application to Spain |
| title |
Integrating long-term economic scenarios into peak load forecasting: An application to Spain |
| spellingShingle |
Integrating long-term economic scenarios into peak load forecasting: An application to Spain Moral Carcedo, Julián Load curve forecasting Long-term scenarios Peak load forecasting Temporal disaggregation Economía |
| title_short |
Integrating long-term economic scenarios into peak load forecasting: An application to Spain |
| title_full |
Integrating long-term economic scenarios into peak load forecasting: An application to Spain |
| title_fullStr |
Integrating long-term economic scenarios into peak load forecasting: An application to Spain |
| title_full_unstemmed |
Integrating long-term economic scenarios into peak load forecasting: An application to Spain |
| title_sort |
Integrating long-term economic scenarios into peak load forecasting: An application to Spain |
| dc.creator.none.fl_str_mv |
Moral Carcedo, Julián Pérez García, Julián |
| author |
Moral Carcedo, Julián |
| author_facet |
Moral Carcedo, Julián Pérez García, Julián |
| author_role |
author |
| author2 |
Pérez García, Julián |
| author2_role |
author |
| dc.contributor.none.fl_str_mv |
Departamento de Análisis Económico: Teoría Económica e Historia Económica Departamento de Economía Aplicada Facultad de Ciencias Económicas y Empresariales |
| dc.subject.none.fl_str_mv |
Load curve forecasting Long-term scenarios Peak load forecasting Temporal disaggregation Economía |
| topic |
Load curve forecasting Long-term scenarios Peak load forecasting Temporal disaggregation Economía |
| description |
The treatment of trend components in electricity demand is critical for long-term peak load forecasting. When forecasting high frequency variables, like daily or hourly loads, a typical problem is how to make long-term scenarios - regarding demographics, GDP growth, etc. - compatible with short-term projections. Traditional procedures that apply de-trending methods are unable to simulate forecasts under alternative long-term scenarios. On the other hand, existing models that allow for changes in long-term trends tend to be characterized by end-of-year discontinuities. In this paper a novel forecasting procedure is presented that improves upon these approaches and is able to combine long and short-term features by employing temporal disaggregation techniques. This method is applied to forecast electricity load for Spain and its performance is compared to that of a nonlinear autoregressive neural network with exogenous inputs. Our proposed procedure is flexible enough to be applied to different scenarios based on alternative assumptions regarding both long-term trends as well as short-term projections |
| publishDate |
2017 |
| dc.date.none.fl_str_mv |
2017 2017-08-30 |
| dc.type.none.fl_str_mv |
research article http://purl.org/coar/resource_type/c_2df8fbb1 AM http://purl.org/coar/version/c_ab4af688f83e57aa |
| dc.type.openaire.fl_str_mv |
info:eu-repo/semantics/article |
| format |
article |
| dc.identifier.none.fl_str_mv |
http://hdl.handle.net/10486/705760 https://dx.doi.org/10.1016/j.energy.2017.08.113 |
| url |
http://hdl.handle.net/10486/705760 https://dx.doi.org/10.1016/j.energy.2017.08.113 |
| dc.language.none.fl_str_mv |
Inglés eng |
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Inglés |
| language |
eng |
| dc.rights.none.fl_str_mv |
open access http://purl.org/coar/access_right/c_abf2 |
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info:eu-repo/semantics/openAccess |
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open access http://purl.org/coar/access_right/c_abf2 |
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openAccess |
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application/pdf |
| dc.publisher.none.fl_str_mv |
Elsevier |
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Elsevier |
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reponame:Biblos-e Archivo. Repositorio Institucional de la UAM instname:Universidad Autónoma de Madrid |
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Universidad Autónoma de Madrid |
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Biblos-e Archivo. Repositorio Institucional de la UAM |
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Biblos-e Archivo. Repositorio Institucional de la UAM |
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