Energy Scheduling Using Decision Trees and Emulation: Agriculture Irrigation with Run-of-the-River Hydroelectricity and a PV Case Study
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.22/16782 |
Resumo: | Agriculture is the very backbone of every country. Unfortunately, agricultural sustainability is threatened by the lack of energy-efficient solutions. The threat becomes more evident with the constantly growing world population. The research community must, therefore, focus on resolving the problem of high energy consumption. This paper proposes a model of energy scheduling in agricultural contexts. Greater energy efficiency is achieved by means of PV (photovoltaics) and hydropower, as demonstrated in the conducted case study. The developed model is intended for contexts where the farm is located near a river, so the farmer can use the flowing water to produce energy. Moreover, the model has been emulated using a variety of state-of-the-art laboratory devices. Optimal energy scheduling is performed via a decision tree approach, optimizing the use of energy resources and reducing electricity costs. Finally, a realistic scenario is presented to show the technical features and the practical behaviors of each emulator when adapting the results of the decision tree. The research outcomes demonstrate the importance of the technical validation of each model. In addition, the results of the emulation reveal practical issues that had not been discovered during the theoretical study or during the simulation |
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Energy Scheduling Using Decision Trees and Emulation: Agriculture Irrigation with Run-of-the-River Hydroelectricity and a PV Case StudyAgricultureDecision treeEnergy schedulingHydropowerRenewablesAgriculture is the very backbone of every country. Unfortunately, agricultural sustainability is threatened by the lack of energy-efficient solutions. The threat becomes more evident with the constantly growing world population. The research community must, therefore, focus on resolving the problem of high energy consumption. This paper proposes a model of energy scheduling in agricultural contexts. Greater energy efficiency is achieved by means of PV (photovoltaics) and hydropower, as demonstrated in the conducted case study. The developed model is intended for contexts where the farm is located near a river, so the farmer can use the flowing water to produce energy. Moreover, the model has been emulated using a variety of state-of-the-art laboratory devices. Optimal energy scheduling is performed via a decision tree approach, optimizing the use of energy resources and reducing electricity costs. Finally, a realistic scenario is presented to show the technical features and the practical behaviors of each emulator when adapting the results of the decision tree. The research outcomes demonstrate the importance of the technical validation of each model. In addition, the results of the emulation reveal practical issues that had not been discovered during the theoretical study or during the simulationhe present research work was conducted and funded within the scope of the following project: Eco Rural IoT project, funded by TETRAMAX-VALUECHAIN-TTX-1, and UID/EEA/00760/2019, funded by FEDER Funds through the COMPETE program and by National Funds through FCT.MDPIRepositório Científico do Instituto Politécnico do PortoAbrishambaf, OmidFaria, PedroVale, ZitaCorchado, Juan M.2021-01-28T15:42:16Z20192019-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/16782eng1996-107310.3390/en12203987info: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:RCAAP2023-03-13T13:04:20Zoai:recipp.ipp.pt:10400.22/16782Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:36:25.169395Repositório 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 |
Energy Scheduling Using Decision Trees and Emulation: Agriculture Irrigation with Run-of-the-River Hydroelectricity and a PV Case Study |
title |
Energy Scheduling Using Decision Trees and Emulation: Agriculture Irrigation with Run-of-the-River Hydroelectricity and a PV Case Study |
spellingShingle |
Energy Scheduling Using Decision Trees and Emulation: Agriculture Irrigation with Run-of-the-River Hydroelectricity and a PV Case Study Abrishambaf, Omid Agriculture Decision tree Energy scheduling Hydropower Renewables |
title_short |
Energy Scheduling Using Decision Trees and Emulation: Agriculture Irrigation with Run-of-the-River Hydroelectricity and a PV Case Study |
title_full |
Energy Scheduling Using Decision Trees and Emulation: Agriculture Irrigation with Run-of-the-River Hydroelectricity and a PV Case Study |
title_fullStr |
Energy Scheduling Using Decision Trees and Emulation: Agriculture Irrigation with Run-of-the-River Hydroelectricity and a PV Case Study |
title_full_unstemmed |
Energy Scheduling Using Decision Trees and Emulation: Agriculture Irrigation with Run-of-the-River Hydroelectricity and a PV Case Study |
title_sort |
Energy Scheduling Using Decision Trees and Emulation: Agriculture Irrigation with Run-of-the-River Hydroelectricity and a PV Case Study |
author |
Abrishambaf, Omid |
author_facet |
Abrishambaf, Omid Faria, Pedro Vale, Zita Corchado, Juan M. |
author_role |
author |
author2 |
Faria, Pedro Vale, Zita Corchado, Juan M. |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Repositório Científico do Instituto Politécnico do Porto |
dc.contributor.author.fl_str_mv |
Abrishambaf, Omid Faria, Pedro Vale, Zita Corchado, Juan M. |
dc.subject.por.fl_str_mv |
Agriculture Decision tree Energy scheduling Hydropower Renewables |
topic |
Agriculture Decision tree Energy scheduling Hydropower Renewables |
description |
Agriculture is the very backbone of every country. Unfortunately, agricultural sustainability is threatened by the lack of energy-efficient solutions. The threat becomes more evident with the constantly growing world population. The research community must, therefore, focus on resolving the problem of high energy consumption. This paper proposes a model of energy scheduling in agricultural contexts. Greater energy efficiency is achieved by means of PV (photovoltaics) and hydropower, as demonstrated in the conducted case study. The developed model is intended for contexts where the farm is located near a river, so the farmer can use the flowing water to produce energy. Moreover, the model has been emulated using a variety of state-of-the-art laboratory devices. Optimal energy scheduling is performed via a decision tree approach, optimizing the use of energy resources and reducing electricity costs. Finally, a realistic scenario is presented to show the technical features and the practical behaviors of each emulator when adapting the results of the decision tree. The research outcomes demonstrate the importance of the technical validation of each model. In addition, the results of the emulation reveal practical issues that had not been discovered during the theoretical study or during the simulation |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019 2019-01-01T00:00:00Z 2021-01-28T15:42:16Z |
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/10400.22/16782 |
url |
http://hdl.handle.net/10400.22/16782 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1996-1073 10.3390/en12203987 |
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 |
MDPI |
publisher.none.fl_str_mv |
MDPI |
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 |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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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 |
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1799131454944313344 |