Probabilistic Rolling-Optimization Control for Coordinating the Operation of Electric Springs in Microgrids with Renewable Distributed Generation

Detalhes bibliográficos
Autor(a) principal: Quijano, Darwin A.
Data de Publicação: 2022
Outros Autores: Padilha-Feltrin, Antonio, Catalao, Joaao P. S.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/TSTE.2022.3188250
http://hdl.handle.net/11449/240469
Resumo: Electric spring (ES) is a novel smart grid technology developed to facilitate the integration of renewable generation by controlling the demand of non-critical loads (NCLs). The utilization of ES to provide a single service such as voltage or frequency regulation, validated in a setup consisting of a single ES, has been extensively investigated. However, to take full advantage of this technology, it is necessary to develop control strategies to coordinate the operation of multiple distributed ESs to provide multiple services in power systems. To this end, this paper presents a rolling-optimization control strategy to coordinate the operation of multiple ESs for voltage regulation, congestion management and cost minimization of the real-time deviations from the scheduled energy exchanges with the grid in microgrids with renewable generation. The strategy is for centralized implementation, and includes a probabilistic optimal power flow-based optimization engine that finds the voltage references of ESs for each control interval taking into account generation variability and uncertainties. NCLs consist of electric water heaters, which are modeled taking into account physical constraints and the hot water demand. Simulations were carried out in two test systems with 14 and 33 buses.
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spelling Probabilistic Rolling-Optimization Control for Coordinating the Operation of Electric Springs in Microgrids with Renewable Distributed GenerationElectric springelectric water heatermicrogridMicrogridsProbabilistic logicReactive powerrenewable energyResistance heatingrolling-optimizationUncertaintyVoltage controlWater heatingElectric spring (ES) is a novel smart grid technology developed to facilitate the integration of renewable generation by controlling the demand of non-critical loads (NCLs). The utilization of ES to provide a single service such as voltage or frequency regulation, validated in a setup consisting of a single ES, has been extensively investigated. However, to take full advantage of this technology, it is necessary to develop control strategies to coordinate the operation of multiple distributed ESs to provide multiple services in power systems. To this end, this paper presents a rolling-optimization control strategy to coordinate the operation of multiple ESs for voltage regulation, congestion management and cost minimization of the real-time deviations from the scheduled energy exchanges with the grid in microgrids with renewable generation. The strategy is for centralized implementation, and includes a probabilistic optimal power flow-based optimization engine that finds the voltage references of ESs for each control interval taking into account generation variability and uncertainties. NCLs consist of electric water heaters, which are modeled taking into account physical constraints and the hot water demand. Simulations were carried out in two test systems with 14 and 33 buses.Universidade Estadual Paulista–UNESP, Ilha Solteira, BrazilFaculty of Engineering, University of Porto, Porto, PortugalUniversidade Estadual Paulista (UNESP)Quijano, Darwin A.Padilha-Feltrin, AntonioCatalao, Joaao P. S.2023-03-01T20:18:33Z2023-03-01T20:18:33Z2022-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1109/TSTE.2022.3188250IEEE Transactions on Sustainable Energy.1949-30371949-3029http://hdl.handle.net/11449/24046910.1109/TSTE.2022.31882502-s2.0-85134255901Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengIEEE Transactions on Sustainable Energyinfo:eu-repo/semantics/openAccess2023-03-01T20:18:33Zoai:repositorio.unesp.br:11449/240469Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-05-23T11:24:53.069865Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Probabilistic Rolling-Optimization Control for Coordinating the Operation of Electric Springs in Microgrids with Renewable Distributed Generation
title Probabilistic Rolling-Optimization Control for Coordinating the Operation of Electric Springs in Microgrids with Renewable Distributed Generation
spellingShingle Probabilistic Rolling-Optimization Control for Coordinating the Operation of Electric Springs in Microgrids with Renewable Distributed Generation
Quijano, Darwin A.
Electric spring
electric water heater
microgrid
Microgrids
Probabilistic logic
Reactive power
renewable energy
Resistance heating
rolling-optimization
Uncertainty
Voltage control
Water heating
title_short Probabilistic Rolling-Optimization Control for Coordinating the Operation of Electric Springs in Microgrids with Renewable Distributed Generation
title_full Probabilistic Rolling-Optimization Control for Coordinating the Operation of Electric Springs in Microgrids with Renewable Distributed Generation
title_fullStr Probabilistic Rolling-Optimization Control for Coordinating the Operation of Electric Springs in Microgrids with Renewable Distributed Generation
title_full_unstemmed Probabilistic Rolling-Optimization Control for Coordinating the Operation of Electric Springs in Microgrids with Renewable Distributed Generation
title_sort Probabilistic Rolling-Optimization Control for Coordinating the Operation of Electric Springs in Microgrids with Renewable Distributed Generation
author Quijano, Darwin A.
author_facet Quijano, Darwin A.
Padilha-Feltrin, Antonio
Catalao, Joaao P. S.
author_role author
author2 Padilha-Feltrin, Antonio
Catalao, Joaao P. S.
author2_role author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv Quijano, Darwin A.
Padilha-Feltrin, Antonio
Catalao, Joaao P. S.
dc.subject.por.fl_str_mv Electric spring
electric water heater
microgrid
Microgrids
Probabilistic logic
Reactive power
renewable energy
Resistance heating
rolling-optimization
Uncertainty
Voltage control
Water heating
topic Electric spring
electric water heater
microgrid
Microgrids
Probabilistic logic
Reactive power
renewable energy
Resistance heating
rolling-optimization
Uncertainty
Voltage control
Water heating
description Electric spring (ES) is a novel smart grid technology developed to facilitate the integration of renewable generation by controlling the demand of non-critical loads (NCLs). The utilization of ES to provide a single service such as voltage or frequency regulation, validated in a setup consisting of a single ES, has been extensively investigated. However, to take full advantage of this technology, it is necessary to develop control strategies to coordinate the operation of multiple distributed ESs to provide multiple services in power systems. To this end, this paper presents a rolling-optimization control strategy to coordinate the operation of multiple ESs for voltage regulation, congestion management and cost minimization of the real-time deviations from the scheduled energy exchanges with the grid in microgrids with renewable generation. The strategy is for centralized implementation, and includes a probabilistic optimal power flow-based optimization engine that finds the voltage references of ESs for each control interval taking into account generation variability and uncertainties. NCLs consist of electric water heaters, which are modeled taking into account physical constraints and the hot water demand. Simulations were carried out in two test systems with 14 and 33 buses.
publishDate 2022
dc.date.none.fl_str_mv 2022-01-01
2023-03-01T20:18:33Z
2023-03-01T20:18:33Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/TSTE.2022.3188250
IEEE Transactions on Sustainable Energy.
1949-3037
1949-3029
http://hdl.handle.net/11449/240469
10.1109/TSTE.2022.3188250
2-s2.0-85134255901
url http://dx.doi.org/10.1109/TSTE.2022.3188250
http://hdl.handle.net/11449/240469
identifier_str_mv IEEE Transactions on Sustainable Energy.
1949-3037
1949-3029
10.1109/TSTE.2022.3188250
2-s2.0-85134255901
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv IEEE Transactions on Sustainable Energy
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
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