Smart Irrigation System Considering Optimal Energy Management Based on Model Predictive Control (MPC).
Traditional irrigation techniques usually cause the wasting of water resources. In addition, crops that are located in rural areas require water pumps that are powered by environmentally un friendly fossil fuels. This research proposes a smart irrigation system energized by a microgrid. The proposal...
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| author | Quimbita Zapata, Wilmer Enrique |
| author2 | Toapaxi Gualpa, Edison Rene |
| author2_role | author |
| author_facet | Quimbita Zapata, Wilmer Enrique Toapaxi Gualpa, Edison Rene |
| author_role | author |
| collection | Repositorio Universidad de las Fuerzas Armadas |
| dc.contributor.none.fl_str_mv | Llanos Proaño, Jacqueline del Rosario |
| dc.creator.none.fl_str_mv | Quimbita Zapata, Wilmer Enrique Toapaxi Gualpa, Edison Rene |
| dc.date.none.fl_str_mv | 2022-07-14T17:09:45Z 2022-07-14T17:09:45Z 2022-05-10 |
| dc.format.none.fl_str_mv | application/pdf application/pdf |
| dc.identifier.none.fl_str_mv | Quimbita Zapata, Wilmer Enrique. Toapaxi Gualpa, Edison Rene (2022). Smart Irrigation System Considering Optimal Energy Management Based on Model Predictive Control (MPC).Maestría en Electrónica y Automatización Mención Redes Industriales. Universidad de las Fuerzas Armadas ESPE. Extensión Latacunga. MEI-0024 http://repositorio.espe.edu.ec/handle/21000/30761 |
| dc.language.none.fl_str_mv | spa |
| dc.publisher.none.fl_str_mv | Universidad de las Fuerzas Armadas ESPE. Maestría en Electrónica y Automatización Mención Redes Industriales. |
| dc.rights.none.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.source.none.fl_str_mv | reponame:Repositorio Universidad de las Fuerzas Armadas instname:Universidad de las Fuerzas Armadas instacron:ESPE |
| dc.subject.none.fl_str_mv | ENERGÍA RENOVABLE RIEGO INTELIGENTE MODELO DE CONTROL PREDICTIVO |
| dc.title.none.fl_str_mv | Smart Irrigation System Considering Optimal Energy Management Based on Model Predictive Control (MPC). |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | Traditional irrigation techniques usually cause the wasting of water resources. In addition, crops that are located in rural areas require water pumps that are powered by environmentally un friendly fossil fuels. This research proposes a smart irrigation system energized by a microgrid. The proposal includes two stages: the first generates the daily irrigation profile based on an expert sys tem for the adequate use of the water. Then, considering the irrigation profile, the power required for the water pump is measured-the optimal daily profile of electricity demand is determined in the second stage. The energy system is a microgrid composed of solar energy, a battery energy stor age system (BESS) and a diesel generator. The microgrid is managed by an energy management system (EMS) that is based on model predictive control (MPC). The system selects the optimal start up time of the water pump considering the technical aspects of irrigation and of the microgrid. The proposed methodology is validated by a simulation with real data from an alfalfa crop in an area of Ecuador. The results show that the smart irrigation proposed considers technical aspects that benefit the growth of the crops being studied and also avoids the waste of water. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | ESPE_c433fbacad93e6d21cf8251f298f6f4f |
| identifier_str_mv | Quimbita Zapata, Wilmer Enrique. Toapaxi Gualpa, Edison Rene (2022). Smart Irrigation System Considering Optimal Energy Management Based on Model Predictive Control (MPC).Maestría en Electrónica y Automatización Mención Redes Industriales. Universidad de las Fuerzas Armadas ESPE. Extensión Latacunga. MEI-0024 |
| instacron_str | ESPE |
| institution | ESPE |
| instname_str | Universidad de las Fuerzas Armadas |
| language | spa |
| network_acronym_str | ESPE |
| network_name_str | Repositorio Universidad de las Fuerzas Armadas |
| oai_identifier_str | oai:repositorio.espe.edu.ec:21000/30761 |
| publishDate | 2022 |
| publisher.none.fl_str_mv | Universidad de las Fuerzas Armadas ESPE. Maestría en Electrónica y Automatización Mención Redes Industriales. |
| reponame_str | Repositorio Universidad de las Fuerzas Armadas |
| repository.mail.fl_str_mv | . |
| repository.name.fl_str_mv | Repositorio Universidad de las Fuerzas Armadas - Universidad de las Fuerzas Armadas |
| repository_id_str | 2042 |
| spelling | Smart Irrigation System Considering Optimal Energy Management Based on Model Predictive Control (MPC).Quimbita Zapata, Wilmer EnriqueToapaxi Gualpa, Edison ReneENERGÍA RENOVABLERIEGO INTELIGENTEMODELO DE CONTROL PREDICTIVOTraditional irrigation techniques usually cause the wasting of water resources. In addition, crops that are located in rural areas require water pumps that are powered by environmentally un friendly fossil fuels. This research proposes a smart irrigation system energized by a microgrid. The proposal includes two stages: the first generates the daily irrigation profile based on an expert sys tem for the adequate use of the water. Then, considering the irrigation profile, the power required for the water pump is measured-the optimal daily profile of electricity demand is determined in the second stage. The energy system is a microgrid composed of solar energy, a battery energy stor age system (BESS) and a diesel generator. The microgrid is managed by an energy management system (EMS) that is based on model predictive control (MPC). The system selects the optimal start up time of the water pump considering the technical aspects of irrigation and of the microgrid. The proposed methodology is validated by a simulation with real data from an alfalfa crop in an area of Ecuador. The results show that the smart irrigation proposed considers technical aspects that benefit the growth of the crops being studied and also avoids the waste of water.ESPE-LUniversidad de las Fuerzas Armadas ESPE. Maestría en Electrónica y Automatización Mención Redes Industriales.Llanos Proaño, Jacqueline del Rosario2022-07-14T17:09:45Z2022-07-14T17:09:45Z2022-05-10info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/pdfQuimbita Zapata, Wilmer Enrique. Toapaxi Gualpa, Edison Rene (2022). Smart Irrigation System Considering Optimal Energy Management Based on Model Predictive Control (MPC).Maestría en Electrónica y Automatización Mención Redes Industriales. Universidad de las Fuerzas Armadas ESPE. Extensión Latacunga.MEI-0024http://repositorio.espe.edu.ec/handle/21000/30761spainfo:eu-repo/semantics/openAccessreponame:Repositorio Universidad de las Fuerzas Armadasinstname:Universidad de las Fuerzas Armadasinstacron:ESPE2024-07-27T11:17:38Zoai:repositorio.espe.edu.ec:21000/30761Institucionalhttps://repositorio.espe.edu.ec/Universidad públicahttps://www.espe.edu.ec/https://repositorio.espe.edu.ec/oai.Ecuador...opendoar:20422026-04-22T15:46:36.718418Repositorio Universidad de las Fuerzas Armadas - Universidad de las Fuerzas Armadastrue |
| spellingShingle | Smart Irrigation System Considering Optimal Energy Management Based on Model Predictive Control (MPC). Quimbita Zapata, Wilmer Enrique ENERGÍA RENOVABLE RIEGO INTELIGENTE MODELO DE CONTROL PREDICTIVO |
| status_str | publishedVersion |
| title | Smart Irrigation System Considering Optimal Energy Management Based on Model Predictive Control (MPC). |
| title_full | Smart Irrigation System Considering Optimal Energy Management Based on Model Predictive Control (MPC). |
| title_fullStr | Smart Irrigation System Considering Optimal Energy Management Based on Model Predictive Control (MPC). |
| title_full_unstemmed | Smart Irrigation System Considering Optimal Energy Management Based on Model Predictive Control (MPC). |
| title_short | Smart Irrigation System Considering Optimal Energy Management Based on Model Predictive Control (MPC). |
| title_sort | Smart Irrigation System Considering Optimal Energy Management Based on Model Predictive Control (MPC). |
| topic | ENERGÍA RENOVABLE RIEGO INTELIGENTE MODELO DE CONTROL PREDICTIVO |
| url | http://repositorio.espe.edu.ec/handle/21000/30761 |