Electricity consumption forecasting using singular spectrum analysis

Singular Spectrum Analysis (SSA) is a non-parametric technique that allows the decomposition of a time series into signal and noise. Thus, it is a useful technique to trend extraction, smooth and filter a time series. The effect on performance of both Box and Jenkins' and Holt-Winters models wh...

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Autores:
Menezes, Moises Lima de
Castro Souza, Reinaldo
Moreira Pessanha, José Francisco
Tipo de recurso:
Article of journal
Fecha de publicación:
2015
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/60744
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/60744
http://bdigital.unal.edu.co/59076/
Palabra clave:
62 Ingeniería y operaciones afines / Engineering
Electricity consumption forecasting
singular spectrum analysis
time series
power system planning
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
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spelling Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Menezes, Moises Lima dee0caaf5e-0adb-4043-96a9-195c6ba74879300Castro Souza, Reinaldo3ee26e1c-4346-444e-9ea3-dc3ef31a4446300Moreira Pessanha, José Franciscof4571222-6512-4523-ad2b-20de871ade303002019-07-02T19:00:52Z2019-07-02T19:00:52Z2015-03-01ISSN: 2346-2183https://repositorio.unal.edu.co/handle/unal/60744http://bdigital.unal.edu.co/59076/Singular Spectrum Analysis (SSA) is a non-parametric technique that allows the decomposition of a time series into signal and noise. Thus, it is a useful technique to trend extraction, smooth and filter a time series. The effect on performance of both Box and Jenkins' and Holt-Winters models when applied to the time series filtered by SSA is investigated in this paper. Three different methodologies are evaluated in the SSA approach: Principal Component Analysis (PCA), Cluster Analysis and Graphical Analysis of Singular Vectors. In order to illustrate and compare the methodologies, in this paper, we also present the main results of a computational experiment with the monthly residential consumption of electricity in Brazil.application/pdfspaUniversidad Nacional de Colombia (Sede Medellín). Facultad de Minas.https://revistas.unal.edu.co/index.php/dyna/article/view/43652Universidad Nacional de Colombia Revistas electrónicas UN DynaDynaMenezes, Moises Lima de and Castro Souza, Reinaldo and Moreira Pessanha, José Francisco (2015) Electricity consumption forecasting using singular spectrum analysis. DYNA, 82 (190). pp. 138-146. ISSN 2346-218362 Ingeniería y operaciones afines / EngineeringElectricity consumption forecastingsingular spectrum analysistime seriespower system planningElectricity consumption forecasting using singular spectrum analysisArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTORIGINAL43652-245780-1-PB.pdfapplication/pdf935389https://repositorio.unal.edu.co/bitstream/unal/60744/1/43652-245780-1-PB.pdf9476d426b5960c0bd1f9e4ba62efb677MD51THUMBNAIL43652-245780-1-PB.pdf.jpg43652-245780-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg9485https://repositorio.unal.edu.co/bitstream/unal/60744/2/43652-245780-1-PB.pdf.jpgdd1d080dd20955f35f46e28e467d0570MD52unal/60744oai:repositorio.unal.edu.co:unal/607442024-04-14 23:11:50.496Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co
dc.title.spa.fl_str_mv Electricity consumption forecasting using singular spectrum analysis
title Electricity consumption forecasting using singular spectrum analysis
spellingShingle Electricity consumption forecasting using singular spectrum analysis
62 Ingeniería y operaciones afines / Engineering
Electricity consumption forecasting
singular spectrum analysis
time series
power system planning
title_short Electricity consumption forecasting using singular spectrum analysis
title_full Electricity consumption forecasting using singular spectrum analysis
title_fullStr Electricity consumption forecasting using singular spectrum analysis
title_full_unstemmed Electricity consumption forecasting using singular spectrum analysis
title_sort Electricity consumption forecasting using singular spectrum analysis
dc.creator.fl_str_mv Menezes, Moises Lima de
Castro Souza, Reinaldo
Moreira Pessanha, José Francisco
dc.contributor.author.spa.fl_str_mv Menezes, Moises Lima de
Castro Souza, Reinaldo
Moreira Pessanha, José Francisco
dc.subject.ddc.spa.fl_str_mv 62 Ingeniería y operaciones afines / Engineering
topic 62 Ingeniería y operaciones afines / Engineering
Electricity consumption forecasting
singular spectrum analysis
time series
power system planning
dc.subject.proposal.spa.fl_str_mv Electricity consumption forecasting
singular spectrum analysis
time series
power system planning
description Singular Spectrum Analysis (SSA) is a non-parametric technique that allows the decomposition of a time series into signal and noise. Thus, it is a useful technique to trend extraction, smooth and filter a time series. The effect on performance of both Box and Jenkins' and Holt-Winters models when applied to the time series filtered by SSA is investigated in this paper. Three different methodologies are evaluated in the SSA approach: Principal Component Analysis (PCA), Cluster Analysis and Graphical Analysis of Singular Vectors. In order to illustrate and compare the methodologies, in this paper, we also present the main results of a computational experiment with the monthly residential consumption of electricity in Brazil.
publishDate 2015
dc.date.issued.spa.fl_str_mv 2015-03-01
dc.date.accessioned.spa.fl_str_mv 2019-07-02T19:00:52Z
dc.date.available.spa.fl_str_mv 2019-07-02T19:00:52Z
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dc.identifier.issn.spa.fl_str_mv ISSN: 2346-2183
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dc.identifier.eprints.spa.fl_str_mv http://bdigital.unal.edu.co/59076/
identifier_str_mv ISSN: 2346-2183
url https://repositorio.unal.edu.co/handle/unal/60744
http://bdigital.unal.edu.co/59076/
dc.language.iso.spa.fl_str_mv spa
language spa
dc.relation.spa.fl_str_mv https://revistas.unal.edu.co/index.php/dyna/article/view/43652
dc.relation.ispartof.spa.fl_str_mv Universidad Nacional de Colombia Revistas electrónicas UN Dyna
Dyna
dc.relation.references.spa.fl_str_mv Menezes, Moises Lima de and Castro Souza, Reinaldo and Moreira Pessanha, José Francisco (2015) Electricity consumption forecasting using singular spectrum analysis. DYNA, 82 (190). pp. 138-146. ISSN 2346-2183
dc.rights.spa.fl_str_mv Derechos reservados - Universidad Nacional de Colombia
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.license.spa.fl_str_mv Atribución-NoComercial 4.0 Internacional
dc.rights.uri.spa.fl_str_mv http://creativecommons.org/licenses/by-nc/4.0/
dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv Atribución-NoComercial 4.0 Internacional
Derechos reservados - Universidad Nacional de Colombia
http://creativecommons.org/licenses/by-nc/4.0/
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Universidad Nacional de Colombia (Sede Medellín). Facultad de Minas.
institution Universidad Nacional de Colombia
bitstream.url.fl_str_mv https://repositorio.unal.edu.co/bitstream/unal/60744/1/43652-245780-1-PB.pdf
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