Analytic Hierarchy Process Algorithm Applied to Battery Energy Storage System Selection for Grid Applications
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Brazilian Archives of Biology and Technology |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132021000200222 |
Resumo: | Abstract The Brazilian Power Sector is preparing the introduction of battery energy storage in its distribution lines for energy quality control. The technical and financial viability of this new technology depends on several factors: battery technologies, geographical locations, environmental restrictions and the local regulation. One of the objectives of the present project was to create a methodology for helping technicians to choose the best battery technology for each particular application. The Analytic Hierarchy Process - AHP algorithm was selected to take into account all the above-mentioned factors. This methodology was applied to a case study considering four different commercially available battery energy storage systems (BESS) and the methodology was able to recommend the best choice by taking into account all the criteria and subcriteria considered. The second objective of the present project is to evaluate a real hybrid BESS operation composed of two different battery technologies. Up to the moment when this paper was submitted the BESS has not been installed yet. The installation place has already been selected, a feeder-line with 1,360 kW peak power, and monitored for energy quality. The BESS has been sized, a 250 kW/1 MWh flow battery together with a 250 kW/500 kWh lithium-ion battery and the purchase process has been initiated. Both battery technologies will work in separate and joint operations for power quality in on-grid and island cases. |
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Analytic Hierarchy Process Algorithm Applied to Battery Energy Storage System Selection for Grid ApplicationsBattery Energy StorageBrazilian Power GridsPeak ShavingVoltage-Sags SmoothingMulticriteria decision-making AlgorithmAnalytic Hierarchy ProcessBattery Technology SelectionAbstract The Brazilian Power Sector is preparing the introduction of battery energy storage in its distribution lines for energy quality control. The technical and financial viability of this new technology depends on several factors: battery technologies, geographical locations, environmental restrictions and the local regulation. One of the objectives of the present project was to create a methodology for helping technicians to choose the best battery technology for each particular application. The Analytic Hierarchy Process - AHP algorithm was selected to take into account all the above-mentioned factors. This methodology was applied to a case study considering four different commercially available battery energy storage systems (BESS) and the methodology was able to recommend the best choice by taking into account all the criteria and subcriteria considered. The second objective of the present project is to evaluate a real hybrid BESS operation composed of two different battery technologies. Up to the moment when this paper was submitted the BESS has not been installed yet. The installation place has already been selected, a feeder-line with 1,360 kW peak power, and monitored for energy quality. The BESS has been sized, a 250 kW/1 MWh flow battery together with a 250 kW/500 kWh lithium-ion battery and the purchase process has been initiated. Both battery technologies will work in separate and joint operations for power quality in on-grid and island cases.Instituto de Tecnologia do Paraná - Tecpar2021-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132021000200222Brazilian Archives of Biology and Technology v.64 n.spe 2021reponame:Brazilian Archives of Biology and Technologyinstname:Instituto de Tecnologia do Paraná (Tecpar)instacron:TECPAR10.1590/1678-4324-75years-2021210148info:eu-repo/semantics/openAccessOening,Ana PaulaMarcilio,Débora CíntiaAndrade,Juliano deImpinnisi,Patricio Rodolfoeng2021-09-10T00:00:00Zoai:scielo:S1516-89132021000200222Revistahttps://www.scielo.br/j/babt/https://old.scielo.br/oai/scielo-oai.phpbabt@tecpar.br||babt@tecpar.br1678-43241516-8913opendoar:2021-09-10T00:00Brazilian Archives of Biology and Technology - Instituto de Tecnologia do Paraná (Tecpar)false |
dc.title.none.fl_str_mv |
Analytic Hierarchy Process Algorithm Applied to Battery Energy Storage System Selection for Grid Applications |
title |
Analytic Hierarchy Process Algorithm Applied to Battery Energy Storage System Selection for Grid Applications |
spellingShingle |
Analytic Hierarchy Process Algorithm Applied to Battery Energy Storage System Selection for Grid Applications Oening,Ana Paula Battery Energy Storage Brazilian Power Grids Peak Shaving Voltage-Sags Smoothing Multicriteria decision-making Algorithm Analytic Hierarchy Process Battery Technology Selection |
title_short |
Analytic Hierarchy Process Algorithm Applied to Battery Energy Storage System Selection for Grid Applications |
title_full |
Analytic Hierarchy Process Algorithm Applied to Battery Energy Storage System Selection for Grid Applications |
title_fullStr |
Analytic Hierarchy Process Algorithm Applied to Battery Energy Storage System Selection for Grid Applications |
title_full_unstemmed |
Analytic Hierarchy Process Algorithm Applied to Battery Energy Storage System Selection for Grid Applications |
title_sort |
Analytic Hierarchy Process Algorithm Applied to Battery Energy Storage System Selection for Grid Applications |
author |
Oening,Ana Paula |
author_facet |
Oening,Ana Paula Marcilio,Débora Cíntia Andrade,Juliano de Impinnisi,Patricio Rodolfo |
author_role |
author |
author2 |
Marcilio,Débora Cíntia Andrade,Juliano de Impinnisi,Patricio Rodolfo |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Oening,Ana Paula Marcilio,Débora Cíntia Andrade,Juliano de Impinnisi,Patricio Rodolfo |
dc.subject.por.fl_str_mv |
Battery Energy Storage Brazilian Power Grids Peak Shaving Voltage-Sags Smoothing Multicriteria decision-making Algorithm Analytic Hierarchy Process Battery Technology Selection |
topic |
Battery Energy Storage Brazilian Power Grids Peak Shaving Voltage-Sags Smoothing Multicriteria decision-making Algorithm Analytic Hierarchy Process Battery Technology Selection |
description |
Abstract The Brazilian Power Sector is preparing the introduction of battery energy storage in its distribution lines for energy quality control. The technical and financial viability of this new technology depends on several factors: battery technologies, geographical locations, environmental restrictions and the local regulation. One of the objectives of the present project was to create a methodology for helping technicians to choose the best battery technology for each particular application. The Analytic Hierarchy Process - AHP algorithm was selected to take into account all the above-mentioned factors. This methodology was applied to a case study considering four different commercially available battery energy storage systems (BESS) and the methodology was able to recommend the best choice by taking into account all the criteria and subcriteria considered. The second objective of the present project is to evaluate a real hybrid BESS operation composed of two different battery technologies. Up to the moment when this paper was submitted the BESS has not been installed yet. The installation place has already been selected, a feeder-line with 1,360 kW peak power, and monitored for energy quality. The BESS has been sized, a 250 kW/1 MWh flow battery together with a 250 kW/500 kWh lithium-ion battery and the purchase process has been initiated. Both battery technologies will work in separate and joint operations for power quality in on-grid and island cases. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132021000200222 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132021000200222 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1678-4324-75years-2021210148 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Instituto de Tecnologia do Paraná - Tecpar |
publisher.none.fl_str_mv |
Instituto de Tecnologia do Paraná - Tecpar |
dc.source.none.fl_str_mv |
Brazilian Archives of Biology and Technology v.64 n.spe 2021 reponame:Brazilian Archives of Biology and Technology instname:Instituto de Tecnologia do Paraná (Tecpar) instacron:TECPAR |
instname_str |
Instituto de Tecnologia do Paraná (Tecpar) |
instacron_str |
TECPAR |
institution |
TECPAR |
reponame_str |
Brazilian Archives of Biology and Technology |
collection |
Brazilian Archives of Biology and Technology |
repository.name.fl_str_mv |
Brazilian Archives of Biology and Technology - Instituto de Tecnologia do Paraná (Tecpar) |
repository.mail.fl_str_mv |
babt@tecpar.br||babt@tecpar.br |
_version_ |
1750318280997863424 |