Comparative analysis of deterministic and probabilistic methods for the integration of distributed generation in power systems
In this article, a comparative analysis is made between three statistical methods (Taguchi’s Orthogonal Array Testing method, Monte Carlo and Two-Point method) by integrating the uncertainty of primary sources of renewable generation in systems of electric power. The modeling of the Institute of Ele...
- Autores:
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2020
- Institución:
- Universidad de Bogotá Jorge Tadeo Lozano
- Repositorio:
- Expeditio: repositorio UTadeo
- Idioma:
- eng
- OAI Identifier:
- oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/27492
- Acceso en línea:
- https://doi.org/10.1016/j.egyr.2019.10.025
http://hdl.handle.net/20.500.12010/27492
http://expeditiorepositorio.utadeo.edu.co
- Palabra clave:
- Distributed generation
Solar power
Wind power
Producción de energía eléctrica
Ingeniería eléctrica
Conversión directa de energía
- Rights
- License
- Abierto (Texto Completo)
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oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/27492 |
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UTADEO2 |
network_name_str |
Expeditio: repositorio UTadeo |
repository_id_str |
|
dc.title.spa.fl_str_mv |
Comparative analysis of deterministic and probabilistic methods for the integration of distributed generation in power systems |
title |
Comparative analysis of deterministic and probabilistic methods for the integration of distributed generation in power systems |
spellingShingle |
Comparative analysis of deterministic and probabilistic methods for the integration of distributed generation in power systems Distributed generation Solar power Wind power Producción de energía eléctrica Ingeniería eléctrica Conversión directa de energía |
title_short |
Comparative analysis of deterministic and probabilistic methods for the integration of distributed generation in power systems |
title_full |
Comparative analysis of deterministic and probabilistic methods for the integration of distributed generation in power systems |
title_fullStr |
Comparative analysis of deterministic and probabilistic methods for the integration of distributed generation in power systems |
title_full_unstemmed |
Comparative analysis of deterministic and probabilistic methods for the integration of distributed generation in power systems |
title_sort |
Comparative analysis of deterministic and probabilistic methods for the integration of distributed generation in power systems |
dc.subject.spa.fl_str_mv |
Distributed generation Solar power Wind power |
topic |
Distributed generation Solar power Wind power Producción de energía eléctrica Ingeniería eléctrica Conversión directa de energía |
dc.subject.lemb.spa.fl_str_mv |
Producción de energía eléctrica Ingeniería eléctrica Conversión directa de energía |
description |
In this article, a comparative analysis is made between three statistical methods (Taguchi’s Orthogonal Array Testing method, Monte Carlo and Two-Point method) by integrating the uncertainty of primary sources of renewable generation in systems of electric power. The modeling of the Institute of Electrical and Electronics Engineers test system of 13 nodes is made by integrating the distributed generation with two different sources: wind and photovoltaic. For the simulation of wind power generation, the wind speed data is from El Cabo de la Vela in the Guajira department in Colombia and for the simulation of solar power generation, the solar radiation data is from Bogota city in Colombia. Once the system of 13 nodes is modeled and incorporated to the variability of primary resource and the load in each case; the load flow can be made by using the Matpower tool in Matlab for each one of the statistical methods proposed. The voltage, power generated, and power demanded data is recovered for each method to create comparison charts, establish the advantages, and disadvantages of each one in the analysis of the distribution of power systems with distributed generation. The main results are: the Taguchi’s Orthogonal Array Testing method improves its behavior if the number of levels is increased for each variable; more iterations in the Montecarlo method produce a greater precision of the probabilities; and the two-point method is a combination between the benefits of the deterministic and the probabilistic. |
publishDate |
2020 |
dc.date.created.none.fl_str_mv |
2020 |
dc.date.accessioned.none.fl_str_mv |
2022-07-11T15:56:05Z |
dc.date.available.none.fl_str_mv |
2022-07-11T15:56:05Z |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.type.local.spa.fl_str_mv |
Artículo |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
format |
http://purl.org/coar/resource_type/c_6501 |
dc.identifier.issn.spa.fl_str_mv |
2352-4847 |
dc.identifier.other.spa.fl_str_mv |
https://doi.org/10.1016/j.egyr.2019.10.025 |
dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/20.500.12010/27492 |
dc.identifier.repourl.spa.fl_str_mv |
http://expeditiorepositorio.utadeo.edu.co |
dc.identifier.doi.spa.fl_str_mv |
https://doi.org/10.1016/j.egyr.2019.10.025 |
dc.identifier.orcid.spa.fl_str_mv |
|
identifier_str_mv |
2352-4847 |
url |
https://doi.org/10.1016/j.egyr.2019.10.025 http://hdl.handle.net/20.500.12010/27492 http://expeditiorepositorio.utadeo.edu.co |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.local.spa.fl_str_mv |
Abierto (Texto Completo) |
rights_invalid_str_mv |
Abierto (Texto Completo) http://purl.org/coar/access_right/c_abf2 |
dc.format.extent.spa.fl_str_mv |
17 páginas |
dc.format.mimetype.spa.fl_str_mv |
application/pdf |
dc.format.rda.spa.fl_str_mv |
1 recurso en línea (archivo de texto) |
dc.coverage.spatial.spa.fl_str_mv |
Colombia |
dc.publisher.spa.fl_str_mv |
Bogotá : Universidad de Bogotá Jorge Tadeo Lozano, 2020 |
institution |
Universidad de Bogotá Jorge Tadeo Lozano |
bitstream.url.fl_str_mv |
https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/27492/2/license.txt https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/27492/3/Captura.PNG |
bitstream.checksum.fl_str_mv |
baba314677a6b940f072575a13bb6906 bf876226964581098d183a78278ddaeb |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 |
repository.name.fl_str_mv |
Repositorio Institucional - Universidad Jorge Tadeo Lozano |
repository.mail.fl_str_mv |
expeditiorepositorio@utadeo.edu.co |
_version_ |
1814213805630029824 |
spelling |
Colombia2022-07-11T15:56:05Z2022-07-11T15:56:05Z20202352-4847https://doi.org/10.1016/j.egyr.2019.10.025http://hdl.handle.net/20.500.12010/27492http://expeditiorepositorio.utadeo.edu.cohttps://doi.org/10.1016/j.egyr.2019.10.025In this article, a comparative analysis is made between three statistical methods (Taguchi’s Orthogonal Array Testing method, Monte Carlo and Two-Point method) by integrating the uncertainty of primary sources of renewable generation in systems of electric power. The modeling of the Institute of Electrical and Electronics Engineers test system of 13 nodes is made by integrating the distributed generation with two different sources: wind and photovoltaic. For the simulation of wind power generation, the wind speed data is from El Cabo de la Vela in the Guajira department in Colombia and for the simulation of solar power generation, the solar radiation data is from Bogota city in Colombia. Once the system of 13 nodes is modeled and incorporated to the variability of primary resource and the load in each case; the load flow can be made by using the Matpower tool in Matlab for each one of the statistical methods proposed. The voltage, power generated, and power demanded data is recovered for each method to create comparison charts, establish the advantages, and disadvantages of each one in the analysis of the distribution of power systems with distributed generation. The main results are: the Taguchi’s Orthogonal Array Testing method improves its behavior if the number of levels is increased for each variable; more iterations in the Montecarlo method produce a greater precision of the probabilities; and the two-point method is a combination between the benefits of the deterministic and the probabilistic.17 páginasapplication/pdf1 recurso en línea (archivo de texto)engBogotá : Universidad de Bogotá Jorge Tadeo Lozano, 2020Distributed generationSolar powerWind powerProducción de energía eléctricaIngeniería eléctricaConversión directa de energíaComparative analysis of deterministic and probabilistic methods for the integration of distributed generation in power systemsArtículoinfo:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Abierto (Texto Completo)http://purl.org/coar/access_right/c_abf2Beltrán, Juan CarlosAristizábal, Andrés JuliánLópez, AlejandraCastaneda, MónicaZapata, SebastiánIvanova, YuliaLICENSElicense.txtlicense.txttext/plain; charset=utf-82938https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/27492/2/license.txtbaba314677a6b940f072575a13bb6906MD52open accessTHUMBNAILCaptura.PNGCaptura.PNGImagenimage/png59194https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/27492/3/Captura.PNGbf876226964581098d183a78278ddaebMD53open access20.500.12010/27492oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/274922022-07-11 10:56:57.224metadata only accessRepositorio Institucional - Universidad Jorge Tadeo Lozanoexpeditiorepositorio@utadeo.edu.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 |