Optimal Power Dispatch of Renewable and NonRenewable Generation through a Second-Order Conic Model
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/EEEIC/ICPSEurope51590.2021.9584817 http://hdl.handle.net/11449/234268 |
Resumo: | This work presents an extension of a second-order conic programming model (SOCP) to handle the multi-objective optimal power dispatch problem considering the probabilistic nature of some parameters related to power demand and the renewable energy sources (RES) generation, such as wind speed and solar irradiation level. Three objective functions are considered in this study: 1) costs of RES and non-RES generation; 2) active power losses in the transmission system; and, 3) emission pollutant gases produced by fossil fuel-based generating units. The stochastic nature of power demands and RES are developed through a set of representative operational scenarios extracted from historical data and via a scenario reduction technique. The results obtained in the SOCP model are compared with a nonlinear programming (NLP) model to check the robustness and precision of SOCP model. To this, both models are implemented and processed to simulate the optimal flow for the IEEE 57- and 118-bus systems. |
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Optimal Power Dispatch of Renewable and NonRenewable Generation through a Second-Order Conic ModelEmission pollutant gasesmulti-objective optimizationoptimal power dispatchrenewable energysecond-order conic programmingThis work presents an extension of a second-order conic programming model (SOCP) to handle the multi-objective optimal power dispatch problem considering the probabilistic nature of some parameters related to power demand and the renewable energy sources (RES) generation, such as wind speed and solar irradiation level. Three objective functions are considered in this study: 1) costs of RES and non-RES generation; 2) active power losses in the transmission system; and, 3) emission pollutant gases produced by fossil fuel-based generating units. The stochastic nature of power demands and RES are developed through a set of representative operational scenarios extracted from historical data and via a scenario reduction technique. The results obtained in the SOCP model are compared with a nonlinear programming (NLP) model to check the robustness and precision of SOCP model. To this, both models are implemented and processed to simulate the optimal flow for the IEEE 57- and 118-bus systems.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Programa Operacional Temático Factores de CompetitividadeFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Department of Electrical Engineering São Paulo State UniversityDepartment of Electrical Engineering and Automation Aalto UniversityPortucalense Univ. Infante D. Henrique INESC TECFaculty of Engineering The University of Porto INESC TECDepartment of Electrical Engineering São Paulo State UniversityPrograma Operacional Temático Factores de Competitividade: 02/SAICT/2017FAPESP: 2015/21972-6FAPESP: 2019/01841-5FAPESP: 2019/23755-3CNPq: 304726/2020-6Programa Operacional Temático Factores de Competitividade: POCI-01-0145-FEDER-029803Universidade Estadual Paulista (UNESP)Aalto UniversityINESC TECdo Carmo Yamaguti, Lucas [UNESP]Home-Ortiz, Juan M. [UNESP]Pourakbari-Kasmaei, MahdiSantos, Sérgio F.Mantovani, José Roberto Sanches [UNESP]Catalão, João P.S.2022-05-01T15:30:01Z2022-05-01T15:30:01Z2021-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1109/EEEIC/ICPSEurope51590.2021.958481721st IEEE International Conference on Environment and Electrical Engineering and 2021 5th IEEE Industrial and Commercial Power System Europe, EEEIC / I and CPS Europe 2021 - Proceedings.http://hdl.handle.net/11449/23426810.1109/EEEIC/ICPSEurope51590.2021.95848172-s2.0-85126437566Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng21st IEEE International Conference on Environment and Electrical Engineering and 2021 5th IEEE Industrial and Commercial Power System Europe, EEEIC / I and CPS Europe 2021 - Proceedingsinfo:eu-repo/semantics/openAccess2024-07-04T19:11:27Zoai:repositorio.unesp.br:11449/234268Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T15:24:15.971624Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Optimal Power Dispatch of Renewable and NonRenewable Generation through a Second-Order Conic Model |
title |
Optimal Power Dispatch of Renewable and NonRenewable Generation through a Second-Order Conic Model |
spellingShingle |
Optimal Power Dispatch of Renewable and NonRenewable Generation through a Second-Order Conic Model do Carmo Yamaguti, Lucas [UNESP] Emission pollutant gases multi-objective optimization optimal power dispatch renewable energy second-order conic programming |
title_short |
Optimal Power Dispatch of Renewable and NonRenewable Generation through a Second-Order Conic Model |
title_full |
Optimal Power Dispatch of Renewable and NonRenewable Generation through a Second-Order Conic Model |
title_fullStr |
Optimal Power Dispatch of Renewable and NonRenewable Generation through a Second-Order Conic Model |
title_full_unstemmed |
Optimal Power Dispatch of Renewable and NonRenewable Generation through a Second-Order Conic Model |
title_sort |
Optimal Power Dispatch of Renewable and NonRenewable Generation through a Second-Order Conic Model |
author |
do Carmo Yamaguti, Lucas [UNESP] |
author_facet |
do Carmo Yamaguti, Lucas [UNESP] Home-Ortiz, Juan M. [UNESP] Pourakbari-Kasmaei, Mahdi Santos, Sérgio F. Mantovani, José Roberto Sanches [UNESP] Catalão, João P.S. |
author_role |
author |
author2 |
Home-Ortiz, Juan M. [UNESP] Pourakbari-Kasmaei, Mahdi Santos, Sérgio F. Mantovani, José Roberto Sanches [UNESP] Catalão, João P.S. |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) Aalto University INESC TEC |
dc.contributor.author.fl_str_mv |
do Carmo Yamaguti, Lucas [UNESP] Home-Ortiz, Juan M. [UNESP] Pourakbari-Kasmaei, Mahdi Santos, Sérgio F. Mantovani, José Roberto Sanches [UNESP] Catalão, João P.S. |
dc.subject.por.fl_str_mv |
Emission pollutant gases multi-objective optimization optimal power dispatch renewable energy second-order conic programming |
topic |
Emission pollutant gases multi-objective optimization optimal power dispatch renewable energy second-order conic programming |
description |
This work presents an extension of a second-order conic programming model (SOCP) to handle the multi-objective optimal power dispatch problem considering the probabilistic nature of some parameters related to power demand and the renewable energy sources (RES) generation, such as wind speed and solar irradiation level. Three objective functions are considered in this study: 1) costs of RES and non-RES generation; 2) active power losses in the transmission system; and, 3) emission pollutant gases produced by fossil fuel-based generating units. The stochastic nature of power demands and RES are developed through a set of representative operational scenarios extracted from historical data and via a scenario reduction technique. The results obtained in the SOCP model are compared with a nonlinear programming (NLP) model to check the robustness and precision of SOCP model. To this, both models are implemented and processed to simulate the optimal flow for the IEEE 57- and 118-bus systems. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-01-01 2022-05-01T15:30:01Z 2022-05-01T15:30:01Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1109/EEEIC/ICPSEurope51590.2021.9584817 21st IEEE International Conference on Environment and Electrical Engineering and 2021 5th IEEE Industrial and Commercial Power System Europe, EEEIC / I and CPS Europe 2021 - Proceedings. http://hdl.handle.net/11449/234268 10.1109/EEEIC/ICPSEurope51590.2021.9584817 2-s2.0-85126437566 |
url |
http://dx.doi.org/10.1109/EEEIC/ICPSEurope51590.2021.9584817 http://hdl.handle.net/11449/234268 |
identifier_str_mv |
21st IEEE International Conference on Environment and Electrical Engineering and 2021 5th IEEE Industrial and Commercial Power System Europe, EEEIC / I and CPS Europe 2021 - Proceedings. 10.1109/EEEIC/ICPSEurope51590.2021.9584817 2-s2.0-85126437566 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
21st IEEE International Conference on Environment and Electrical Engineering and 2021 5th IEEE Industrial and Commercial Power System Europe, EEEIC / I and CPS Europe 2021 - Proceedings |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128510548508672 |