Carbon Footprint Management: A Pathway Toward Smart Emission Abatement
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/TII.2019.2922394 http://hdl.handle.net/11449/196710 |
Resumo: | There is an increasing concern about controlling and reducing carbon emissions in power systems. In this regard, researchers have focused on managing emissions on the generation side, which is the main source of emissions. Considering emission limits on the generation side result in an increase in locational marginal prices that negatively affects social welfare. However, carbon emissions are a by-product of electricity generation that is used to satisfy the demands on the consumer side. Consequently, demand-side emission control may not be achieved if only the generation is taken into account. In order to fill this existing gap, in this paper, a demand-side management approach aiming at carbon footprint control is proposed. First, the carbon footprint is allocated among the consumers using an improved proportional sharing theorem method. Each consumer learns about their real-time carbon footprint, excess carbon footprint, and the incurred surcharge tax. Then, demands are adjusted via a proper adjustment procedure. This provides enough information for consumers where demand management may result in carbon footprint and demand reductions as well as the exemption of incurred taxes. Profit analysis for both generation and demand sides is carried out to show the effectiveness of the proposed framework using two illustrative case studies. The results obtained, compared with existing policies such as carbon cap, cap-and-trade, and carbon tax, prove the fairness and the advantages of the proposed model for both the demand and the generation sides. |
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Carbon Footprint Management: A Pathway Toward Smart Emission AbatementCarbon abatementcarbon footprint allocationdemand side managementpower tracingtax exemptionThere is an increasing concern about controlling and reducing carbon emissions in power systems. In this regard, researchers have focused on managing emissions on the generation side, which is the main source of emissions. Considering emission limits on the generation side result in an increase in locational marginal prices that negatively affects social welfare. However, carbon emissions are a by-product of electricity generation that is used to satisfy the demands on the consumer side. Consequently, demand-side emission control may not be achieved if only the generation is taken into account. In order to fill this existing gap, in this paper, a demand-side management approach aiming at carbon footprint control is proposed. First, the carbon footprint is allocated among the consumers using an improved proportional sharing theorem method. Each consumer learns about their real-time carbon footprint, excess carbon footprint, and the incurred surcharge tax. Then, demands are adjusted via a proper adjustment procedure. This provides enough information for consumers where demand management may result in carbon footprint and demand reductions as well as the exemption of incurred taxes. Profit analysis for both generation and demand sides is carried out to show the effectiveness of the proposed framework using two illustrative case studies. The results obtained, compared with existing policies such as carbon cap, cap-and-trade, and carbon tax, prove the fairness and the advantages of the proposed model for both the demand and the generation sides.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Aalto Univ, Dept Elect Engn, Espoo 02150, FinlandUniv Castilla La Mancha, ETS Ingenieros Ind, E-13071 Ciudad Real, SpainSao Paulo State Univ, Dept Elect Engn, BR-15385000 Ilha Solteira, BrazilSao Paulo State Univ, Dept Elect Engn, BR-15385000 Ilha Solteira, BrazilFAPESP: 2014/22828-3FAPESP: 2015/21972-6FAPESP: 2016/14319-7CNPq: 305318/2016-0Ieee-inst Electrical Electronics Engineers IncAalto UnivUniv Castilla La ManchaUniversidade Estadual Paulista (Unesp)Pourakbari-Kasmaei, MahdiLehtonen, MattiContreras, JavierSanches Mantovani, Jose Roberto [UNESP]2020-12-10T19:53:46Z2020-12-10T19:53:46Z2020-02-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article935-948http://dx.doi.org/10.1109/TII.2019.2922394Ieee Transactions On Industrial Informatics. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 16, n. 2, p. 935-948, 2020.1551-3203http://hdl.handle.net/11449/19671010.1109/TII.2019.2922394WOS:000521337000019Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengIeee Transactions On Industrial Informaticsinfo:eu-repo/semantics/openAccess2024-07-04T19:06:57Zoai:repositorio.unesp.br:11449/196710Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:32:38.396833Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Carbon Footprint Management: A Pathway Toward Smart Emission Abatement |
title |
Carbon Footprint Management: A Pathway Toward Smart Emission Abatement |
spellingShingle |
Carbon Footprint Management: A Pathway Toward Smart Emission Abatement Pourakbari-Kasmaei, Mahdi Carbon abatement carbon footprint allocation demand side management power tracing tax exemption |
title_short |
Carbon Footprint Management: A Pathway Toward Smart Emission Abatement |
title_full |
Carbon Footprint Management: A Pathway Toward Smart Emission Abatement |
title_fullStr |
Carbon Footprint Management: A Pathway Toward Smart Emission Abatement |
title_full_unstemmed |
Carbon Footprint Management: A Pathway Toward Smart Emission Abatement |
title_sort |
Carbon Footprint Management: A Pathway Toward Smart Emission Abatement |
author |
Pourakbari-Kasmaei, Mahdi |
author_facet |
Pourakbari-Kasmaei, Mahdi Lehtonen, Matti Contreras, Javier Sanches Mantovani, Jose Roberto [UNESP] |
author_role |
author |
author2 |
Lehtonen, Matti Contreras, Javier Sanches Mantovani, Jose Roberto [UNESP] |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Aalto Univ Univ Castilla La Mancha Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Pourakbari-Kasmaei, Mahdi Lehtonen, Matti Contreras, Javier Sanches Mantovani, Jose Roberto [UNESP] |
dc.subject.por.fl_str_mv |
Carbon abatement carbon footprint allocation demand side management power tracing tax exemption |
topic |
Carbon abatement carbon footprint allocation demand side management power tracing tax exemption |
description |
There is an increasing concern about controlling and reducing carbon emissions in power systems. In this regard, researchers have focused on managing emissions on the generation side, which is the main source of emissions. Considering emission limits on the generation side result in an increase in locational marginal prices that negatively affects social welfare. However, carbon emissions are a by-product of electricity generation that is used to satisfy the demands on the consumer side. Consequently, demand-side emission control may not be achieved if only the generation is taken into account. In order to fill this existing gap, in this paper, a demand-side management approach aiming at carbon footprint control is proposed. First, the carbon footprint is allocated among the consumers using an improved proportional sharing theorem method. Each consumer learns about their real-time carbon footprint, excess carbon footprint, and the incurred surcharge tax. Then, demands are adjusted via a proper adjustment procedure. This provides enough information for consumers where demand management may result in carbon footprint and demand reductions as well as the exemption of incurred taxes. Profit analysis for both generation and demand sides is carried out to show the effectiveness of the proposed framework using two illustrative case studies. The results obtained, compared with existing policies such as carbon cap, cap-and-trade, and carbon tax, prove the fairness and the advantages of the proposed model for both the demand and the generation sides. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-12-10T19:53:46Z 2020-12-10T19:53:46Z 2020-02-01 |
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/TII.2019.2922394 Ieee Transactions On Industrial Informatics. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 16, n. 2, p. 935-948, 2020. 1551-3203 http://hdl.handle.net/11449/196710 10.1109/TII.2019.2922394 WOS:000521337000019 |
url |
http://dx.doi.org/10.1109/TII.2019.2922394 http://hdl.handle.net/11449/196710 |
identifier_str_mv |
Ieee Transactions On Industrial Informatics. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 16, n. 2, p. 935-948, 2020. 1551-3203 10.1109/TII.2019.2922394 WOS:000521337000019 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Ieee Transactions On Industrial Informatics |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
935-948 |
dc.publisher.none.fl_str_mv |
Ieee-inst Electrical Electronics Engineers Inc |
publisher.none.fl_str_mv |
Ieee-inst Electrical Electronics Engineers Inc |
dc.source.none.fl_str_mv |
Web of Science 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_ |
1808128240013803520 |