A local search algorithm to allocate loads predicted by spatial load forecasting studies
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , |
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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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 |
|
_version_ |
1808129149636706304 |