Power generation investmen : An algorithm to get a good feasible solution from operation simulations.

The algorithm we present here is able to give an optimal solution for the power generation expansion problem if there is no dynamical links between time steps (normally years). In other case, it gives a good approximation to the optimal solution. It uses as input an estimation of the expected operat...

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Autor principal: Tasende, Daniel (author)
Formato: masterThesis
Idioma:inglês
Publicado em: 2002
Assuntos:
Acesso em linha:https://hdl.handle.net/20.500.12008/24376
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author Tasende, Daniel
author_browse Tasende, Daniel
author_facet Tasende, Daniel
author_role author
collection COLIBRI
dc.contributor.none.fl_str_mv Tasende Daniel, Universidad de la República (Uruguay). Facultad de Ingeniería.
dc.creator.none.fl_str_mv Tasende, Daniel
dc.date.none.fl_str_mv 2002
2020-06-19T16:41:03Z
2020-06-19T16:41:03Z
dc.format.none.fl_str_mv 36 p.
application/pdf
dc.identifier.none.fl_str_mv Tasende, D. Power generation investmen : An algorithm to get a good feasible solution from operation simulations [en línea] Tesis de maestría. Montevideo : Udelar. FI, 2002.
1688-2792
https://hdl.handle.net/20.500.12008/24376
dc.language.none.fl_str_mv en
eng
dc.publisher.none.fl_str_mv Udelar.FI.
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
dc.source.none.fl_str_mv reponame:COLIBRI
instname:Universidad de la República
instacron:Universidad de la República
dc.subject.none.fl_str_mv GENERACION DE ENERGIA
OPTIMIZACION
PROBABILIDAD
ALGORITMOS
dc.title.none.fl_str_mv Power generation investmen : An algorithm to get a good feasible solution from operation simulations.
dc.type.none.fl_str_mv Tesis de maestría
info:eu-repo/semantics/masterThesis
info:eu-repo/semantics/acceptedVersion
description The algorithm we present here is able to give an optimal solution for the power generation expansion problem if there is no dynamical links between time steps (normally years). In other case, it gives a good approximation to the optimal solution. It uses as input an estimation of the expected operation cost with fixed generation equipment. This kind of data is normally available in Power Utilities, frequently from operation models. For the general problem (solved with more involved methods), this algorithm can give a good feasible solution that can be useful in the search for the optimum.
eu_rights_str_mv openAccess
format masterThesis
id anni_e060d1a9d8e59a71d33bdbdca95c13ef
identifier_str_mv Tasende, D. Power generation investmen : An algorithm to get a good feasible solution from operation simulations [en línea] Tesis de maestría. Montevideo : Udelar. FI, 2002.
1688-2792
instacron_str Universidad de la República
institution Universidad de la República
instname_str Universidad de la República
language eng
language_invalid_str_mv en
network_acronym_str anni
network_name_str oai-lr-anni
oai_identifier_str oai:colibri.udelar.edu.uy:20.500.12008/24376
publishDate 2002
publishDateSort 2002
publisher.none.fl_str_mv Udelar.FI.
reponame_str COLIBRI
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
spelling Power generation investmen : An algorithm to get a good feasible solution from operation simulations.Tasende, DanielGENERACION DE ENERGIAOPTIMIZACIONPROBABILIDADALGORITMOSThe algorithm we present here is able to give an optimal solution for the power generation expansion problem if there is no dynamical links between time steps (normally years). In other case, it gives a good approximation to the optimal solution. It uses as input an estimation of the expected operation cost with fixed generation equipment. This kind of data is normally available in Power Utilities, frequently from operation models. For the general problem (solved with more involved methods), this algorithm can give a good feasible solution that can be useful in the search for the optimum.Udelar.FI.Tasende Daniel, Universidad de la República (Uruguay). Facultad de Ingeniería.2020-06-19T16:41:03Z2020-06-19T16:41:03Z2002Tesis de maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersion36 p.application/pdfTasende, D. Power generation investmen : An algorithm to get a good feasible solution from operation simulations [en línea] Tesis de maestría. Montevideo : Udelar. FI, 2002.1688-2792https://hdl.handle.net/20.500.12008/24376reponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaenengLas obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)oai:colibri.udelar.edu.uy:20.500.12008/243762026-04-14T10:27:33Z
spellingShingle Power generation investmen : An algorithm to get a good feasible solution from operation simulations.
Tasende, Daniel
GENERACION DE ENERGIA
OPTIMIZACION
PROBABILIDAD
ALGORITMOS
status_str acceptedVersion
title Power generation investmen : An algorithm to get a good feasible solution from operation simulations.
title_full Power generation investmen : An algorithm to get a good feasible solution from operation simulations.
title_fullStr Power generation investmen : An algorithm to get a good feasible solution from operation simulations.
title_full_unstemmed Power generation investmen : An algorithm to get a good feasible solution from operation simulations.
title_short Power generation investmen : An algorithm to get a good feasible solution from operation simulations.
title_sort Power generation investmen : An algorithm to get a good feasible solution from operation simulations.
topic GENERACION DE ENERGIA
OPTIMIZACION
PROBABILIDAD
ALGORITMOS
url https://hdl.handle.net/20.500.12008/24376