A local search algorithm to allocate loads predicted by spatial load forecasting studies

Detalhes bibliográficos
Autor(a) principal: Melo, Joel D.
Data de Publicação: 2017
Outros Autores: Zambrano-Asanza, Sergio, Padilha-Feltrin, Antonio [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1016/j.epsr.2017.01.020
http://hdl.handle.net/11449/178627
Resumo: In recent years, spatial load forecasting studies have helped to direct the expansion of the distribution systems in cities with rapid urban growth, providing maps that showing the spatial distribution of expected load. However, these maps do not allow to determine how load varies on the existing network elements. This information is important to define the reinforcements or the installation of new facilities in the electrical distribution network. In order to help planners in such decisions, a search method to allocate the loads resulting from spatial load forecasting studies is presented. This method treats each of these forecast loads as new load center to be connected to an existing distribution feeder. To find the path from a load center, the proposed method uses a list of its nearby feeders. Allocation depends on the path cost function, which is calculated based on the supply capability of the network elements. The proposal chooses the shortest path with sufficient capacity to supply the new load, i.e., it finds the path with minimal cost function for list of nearby feeders. The result is the final available capability of existing networks (after the allocation process) to supply the expected loads in the geographic area. The method is tested using the results of a spatial load forecast for a real distribution system in a medium-sized Brazilian city. In this test system, the load allocation influenced the number of network elements to be reinforced. The proposal was compared to commercial software, showing a configuration with smaller numbers of overload elements and a lower cost of expansion to the most overloaded feeders.
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spelling A local search algorithm to allocate loads predicted by spatial load forecasting studiesGeographic information systemPower distribution system planningShortest-path methodSpatial load forecastingIn recent years, spatial load forecasting studies have helped to direct the expansion of the distribution systems in cities with rapid urban growth, providing maps that showing the spatial distribution of expected load. However, these maps do not allow to determine how load varies on the existing network elements. This information is important to define the reinforcements or the installation of new facilities in the electrical distribution network. In order to help planners in such decisions, a search method to allocate the loads resulting from spatial load forecasting studies is presented. This method treats each of these forecast loads as new load center to be connected to an existing distribution feeder. To find the path from a load center, the proposed method uses a list of its nearby feeders. Allocation depends on the path cost function, which is calculated based on the supply capability of the network elements. The proposal chooses the shortest path with sufficient capacity to supply the new load, i.e., it finds the path with minimal cost function for list of nearby feeders. The result is the final available capability of existing networks (after the allocation process) to supply the expected loads in the geographic area. The method is tested using the results of a spatial load forecast for a real distribution system in a medium-sized Brazilian city. In this test system, the load allocation influenced the number of network elements to be reinforced. The proposal was compared to commercial software, showing a configuration with smaller numbers of overload elements and a lower cost of expansion to the most overloaded feeders.The Engineering Modeling and Applied Social Sciences Center Federal University of ABC— UFABCPlanning Department the CENTROSUR Distribution UtilityDepartment of Electrical Engineering Sao Paulo State University—UNESPDepartment of Electrical Engineering Sao Paulo State University—UNESPUniversidade Federal do ABC (UFABC)the CENTROSUR Distribution UtilityUniversidade Estadual Paulista (Unesp)Melo, Joel D.Zambrano-Asanza, SergioPadilha-Feltrin, Antonio [UNESP]2018-12-11T17:31:23Z2018-12-11T17:31:23Z2017-05-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article206-217application/pdfhttp://dx.doi.org/10.1016/j.epsr.2017.01.020Electric Power Systems Research, v. 146, p. 206-217.0378-7796http://hdl.handle.net/11449/17862710.1016/j.epsr.2017.01.0202-s2.0-850118906352-s2.0-85011890635.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengElectric Power Systems Research1,048info:eu-repo/semantics/openAccess2024-07-04T19:06:35Zoai:repositorio.unesp.br:11449/178627Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:00:46.004536Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A local search algorithm to allocate loads predicted by spatial load forecasting studies
title A local search algorithm to allocate loads predicted by spatial load forecasting studies
spellingShingle A local search algorithm to allocate loads predicted by spatial load forecasting studies
Melo, Joel D.
Geographic information system
Power distribution system planning
Shortest-path method
Spatial load forecasting
title_short A local search algorithm to allocate loads predicted by spatial load forecasting studies
title_full A local search algorithm to allocate loads predicted by spatial load forecasting studies
title_fullStr A local search algorithm to allocate loads predicted by spatial load forecasting studies
title_full_unstemmed A local search algorithm to allocate loads predicted by spatial load forecasting studies
title_sort A local search algorithm to allocate loads predicted by spatial load forecasting studies
author Melo, Joel D.
author_facet Melo, Joel D.
Zambrano-Asanza, Sergio
Padilha-Feltrin, Antonio [UNESP]
author_role author
author2 Zambrano-Asanza, Sergio
Padilha-Feltrin, Antonio [UNESP]
author2_role author
author
dc.contributor.none.fl_str_mv Universidade Federal do ABC (UFABC)
the CENTROSUR Distribution Utility
Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Melo, Joel D.
Zambrano-Asanza, Sergio
Padilha-Feltrin, Antonio [UNESP]
dc.subject.por.fl_str_mv Geographic information system
Power distribution system planning
Shortest-path method
Spatial load forecasting
topic Geographic information system
Power distribution system planning
Shortest-path method
Spatial load forecasting
description In recent years, spatial load forecasting studies have helped to direct the expansion of the distribution systems in cities with rapid urban growth, providing maps that showing the spatial distribution of expected load. However, these maps do not allow to determine how load varies on the existing network elements. This information is important to define the reinforcements or the installation of new facilities in the electrical distribution network. In order to help planners in such decisions, a search method to allocate the loads resulting from spatial load forecasting studies is presented. This method treats each of these forecast loads as new load center to be connected to an existing distribution feeder. To find the path from a load center, the proposed method uses a list of its nearby feeders. Allocation depends on the path cost function, which is calculated based on the supply capability of the network elements. The proposal chooses the shortest path with sufficient capacity to supply the new load, i.e., it finds the path with minimal cost function for list of nearby feeders. The result is the final available capability of existing networks (after the allocation process) to supply the expected loads in the geographic area. The method is tested using the results of a spatial load forecast for a real distribution system in a medium-sized Brazilian city. In this test system, the load allocation influenced the number of network elements to be reinforced. The proposal was compared to commercial software, showing a configuration with smaller numbers of overload elements and a lower cost of expansion to the most overloaded feeders.
publishDate 2017
dc.date.none.fl_str_mv 2017-05-01
2018-12-11T17:31:23Z
2018-12-11T17:31:23Z
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/10.1016/j.epsr.2017.01.020
Electric Power Systems Research, v. 146, p. 206-217.
0378-7796
http://hdl.handle.net/11449/178627
10.1016/j.epsr.2017.01.020
2-s2.0-85011890635
2-s2.0-85011890635.pdf
url http://dx.doi.org/10.1016/j.epsr.2017.01.020
http://hdl.handle.net/11449/178627
identifier_str_mv Electric Power Systems Research, v. 146, p. 206-217.
0378-7796
10.1016/j.epsr.2017.01.020
2-s2.0-85011890635
2-s2.0-85011890635.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Electric Power Systems Research
1,048
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 206-217
application/pdf
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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