Probabilistic Rolling-Optimization Control for Coordinating the Operation of Electric Springs in Microgrids with Renewable Distributed Generation
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , |
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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Repositório Institucional da UNESP |
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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:29462023-03-01T20:18:33Repositório 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 |
|
_version_ |
1803649306005078016 |