Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment
Main Author: | |
---|---|
Publication Date: | 2014 |
Other Authors: | , , |
Format: | Article |
Language: | eng |
Source: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Download full: | http://hdl.handle.net/10400.22/5247 |
Summary: | Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management. |
id |
RCAP_2734184f2f289396aac8cfc077742789 |
---|---|
oai_identifier_str |
oai:recipp.ipp.pt:10400.22/5247 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid EnvironmentDistributed generationPower demand curveMixed-integer linear programmingSmart gridVehicle-to-gridSmart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management.ElsevierRepositório Científico do Instituto Politécnico do PortoMorais, HugoSousa, TiagoVale, ZitaFaria, Pedro2014-12-09T15:22:47Z20142014-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/5247eng0196-890410.1016/j.enconman.2014.03.032info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-13T12:45:16Zoai:recipp.ipp.pt:10400.22/5247Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:25:56.624799Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment |
title |
Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment |
spellingShingle |
Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment Morais, Hugo Distributed generation Power demand curve Mixed-integer linear programming Smart grid Vehicle-to-grid |
title_short |
Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment |
title_full |
Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment |
title_fullStr |
Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment |
title_full_unstemmed |
Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment |
title_sort |
Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment |
author |
Morais, Hugo |
author_facet |
Morais, Hugo Sousa, Tiago Vale, Zita Faria, Pedro |
author_role |
author |
author2 |
Sousa, Tiago Vale, Zita Faria, Pedro |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Repositório Científico do Instituto Politécnico do Porto |
dc.contributor.author.fl_str_mv |
Morais, Hugo Sousa, Tiago Vale, Zita Faria, Pedro |
dc.subject.por.fl_str_mv |
Distributed generation Power demand curve Mixed-integer linear programming Smart grid Vehicle-to-grid |
topic |
Distributed generation Power demand curve Mixed-integer linear programming Smart grid Vehicle-to-grid |
description |
Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-12-09T15:22:47Z 2014 2014-01-01T00:00:00Z |
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://hdl.handle.net/10400.22/5247 |
url |
http://hdl.handle.net/10400.22/5247 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0196-8904 10.1016/j.enconman.2014.03.032 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799131353793429504 |