Artificial intelligence for energetic potential analysis in Colombia
Climate change and pollution have driven the consumption of cleaner energy sources for the past years. Solar energy, has been one of the main demanded and efficient renewable energy sources. Therefore there has been great interest in innovation towards better allocation of the solar resource. In Col...
- Autores:
-
Acosta Cevallos, Paulina Michelle
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2020
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/51540
- Acceso en línea:
- http://hdl.handle.net/1992/51540
- Palabra clave:
- Inteligencia artificial
Recursos energúticos renovables
Radiación solar
Ingeniería
- Rights
- openAccess
- License
- https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdf
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Artificial intelligence for energetic potential analysis in Colombia |
| title |
Artificial intelligence for energetic potential analysis in Colombia |
| spellingShingle |
Artificial intelligence for energetic potential analysis in Colombia Inteligencia artificial Recursos energúticos renovables Radiación solar Ingeniería |
| title_short |
Artificial intelligence for energetic potential analysis in Colombia |
| title_full |
Artificial intelligence for energetic potential analysis in Colombia |
| title_fullStr |
Artificial intelligence for energetic potential analysis in Colombia |
| title_full_unstemmed |
Artificial intelligence for energetic potential analysis in Colombia |
| title_sort |
Artificial intelligence for energetic potential analysis in Colombia |
| dc.creator.fl_str_mv |
Acosta Cevallos, Paulina Michelle |
| dc.contributor.advisor.none.fl_str_mv |
Giraldo Trujillo, Luis Felipe Narváez Morales, Gabriel Esteban |
| dc.contributor.author.none.fl_str_mv |
Acosta Cevallos, Paulina Michelle |
| dc.contributor.jury.none.fl_str_mv |
Bressan, Michael |
| dc.subject.armarc.spa.fl_str_mv |
Inteligencia artificial Recursos energúticos renovables Radiación solar |
| topic |
Inteligencia artificial Recursos energúticos renovables Radiación solar Ingeniería |
| dc.subject.themes.none.fl_str_mv |
Ingeniería |
| description |
Climate change and pollution have driven the consumption of cleaner energy sources for the past years. Solar energy, has been one of the main demanded and efficient renewable energy sources. Therefore there has been great interest in innovation towards better allocation of the solar resource. In Colombia, around 40% of the country is a ZNI (Not Interconnected Zone), meaning this locations dont have access to the national electrical wiring, generally due to the lack of electrical infrastructure as they are not easily accesible locations, with low capital and are situated in rural areas.Hence, they are highly dependent on solar energy in order to supply their energy consumption thus the importance of efficient allocation of the solar resource. Consequently, this paper proposes the creation of a solar irradiation open source atlas that provides information of the solar resource and other metereological variables on 64,000 points located in Colombia, separated by a 4km2 radius for each year from 1998 to 2019 in 30 minute intervals supplied by the NSRDB. Furthermore, this atlas would provide solar irradiation forecasting, predicting to different time horizons. Even though, solar irradiation forecasting has been widely studied, this paper explores a method in which information from different geographical points can be fusioned in order to improve the prediction of solar irradiation at a given point and time horizon.Then proposing a framework that considers the combination of spatial and temporal information by using attention modules in a LSTM network. |
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2020 |
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2020 |
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2021-08-10T18:30:00Z |
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2021-08-10T18:30:00Z |
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Trabajo de grado - Pregrado |
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23304.pdf |
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eng |
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eng |
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8 hojas |
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Universidad de los Andes |
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Ingeniería Electrónica |
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Facultad de Ingeniería |
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Departamento de Ingeniería Eléctrica y Electrónica |
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Universidad de los Andes |
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Al consultar y hacer uso de este recurso, está aceptando las condiciones de uso establecidas por los autores.https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdfinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Giraldo Trujillo, Luis Felipe2af401d9-d9aa-46a3-b105-dbd811b6b8da400Narváez Morales, Gabriel Esteban7ac5997f-fbf1-43d6-bef8-4d25cca9deb9500Acosta Cevallos, Paulina Michelle74a29c9b-417c-4cd4-a403-9598587ff69d500Bressan, Michael2021-08-10T18:30:00Z2021-08-10T18:30:00Z2020http://hdl.handle.net/1992/5154023304.pdfinstname:Universidad de los Andesreponame:Repositorio Institucional Sénecarepourl:https://repositorio.uniandes.edu.co/Climate change and pollution have driven the consumption of cleaner energy sources for the past years. Solar energy, has been one of the main demanded and efficient renewable energy sources. Therefore there has been great interest in innovation towards better allocation of the solar resource. In Colombia, around 40% of the country is a ZNI (Not Interconnected Zone), meaning this locations dont have access to the national electrical wiring, generally due to the lack of electrical infrastructure as they are not easily accesible locations, with low capital and are situated in rural areas.Hence, they are highly dependent on solar energy in order to supply their energy consumption thus the importance of efficient allocation of the solar resource. Consequently, this paper proposes the creation of a solar irradiation open source atlas that provides information of the solar resource and other metereological variables on 64,000 points located in Colombia, separated by a 4km2 radius for each year from 1998 to 2019 in 30 minute intervals supplied by the NSRDB. Furthermore, this atlas would provide solar irradiation forecasting, predicting to different time horizons. Even though, solar irradiation forecasting has been widely studied, this paper explores a method in which information from different geographical points can be fusioned in order to improve the prediction of solar irradiation at a given point and time horizon.Then proposing a framework that considers the combination of spatial and temporal information by using attention modules in a LSTM network.El cambio climático y la contaminación han impulsado la consumo de fuentes de energía más limpias durante los últimos años. La energía solar, ha sido una de las principales demandadas y eficientes Fuentes de energía renovable. Por tanto ha habido grandes interés en la innovación para una mejor asignación de la energía solar recurso. En Colombia, alrededor del 40% del país es ZNI (No Zona interconectada), lo que significa que estas ubicaciones no tienen acceso al cableado eléctrico nacional, generalmente debido a la falta de infraestructura eléctrica ya que no son lugares de fácil acceso, con escaso capital y están situadas en zonas rurales. dependen en gran medida de la energía solar para abastecer sus el consumo de energía de ahí la importancia de una asignación eficiente del recurso solar. En consecuencia, este trabajo propone la creación de un solar atlas de código abierto de irradiación que proporciona información recurso solar y otras variables meteorológicas en 64.000 puntos ubicada en Colombia, separada por 4km2 radio para cada año de 1998 a 2019 en intervalos de 30 minutos suministrados por el NSRDB. Además, este atlas proporcionaría radiación solar pronosticar, predecir a diferentes horizontes de tiempo. Aunque, El pronóstico de la irradiación solar ha sido ampliamente estudiado, este artículo Explora un método en el que se puede fusionar información de diferentes puntos geográficos para mejorar la predicción de irradiación solar en un punto y horizonte de tiempo dados, proponiendo un marco que considere la combinación de espacios e información temporal mediante el uso de módulos de atención en un LSTM red.Ingeniero ElectrónicoPregrado8 hojasapplication/pdfengUniversidad de los AndesIngeniería ElectrónicaFacultad de IngenieríaDepartamento de Ingeniería Eléctrica y ElectrónicaArtificial intelligence for energetic potential analysis in ColombiaTrabajo de grado - Pregradoinfo:eu-repo/semantics/bachelorThesishttp://purl.org/coar/resource_type/c_7a1fhttp://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/TPInteligencia artificialRecursos energúticos renovablesRadiación solarIngeniería201710937PublicationORIGINAL23304.pdfapplication/pdf4314504https://repositorio.uniandes.edu.co/bitstreams/5bd6153f-c413-401d-add2-c099fce19275/downloadf0e0e4dcbc05d1d6e633839bb9713a9dMD51TEXT23304.pdf.txt23304.pdf.txtExtracted texttext/plain27753https://repositorio.uniandes.edu.co/bitstreams/893ed386-8567-414f-b0a3-89dfc0fbdb9f/downloada692dc099c5983b9c35a16bbeaa8e974MD54THUMBNAIL23304.pdf.jpg23304.pdf.jpgIM Thumbnailimage/jpeg29893https://repositorio.uniandes.edu.co/bitstreams/f3a71757-b7d6-4a59-8f17-341cf3474a38/downloada40f17d5d8218be30d1d24f1e6c50ba6MD551992/51540oai:repositorio.uniandes.edu.co:1992/515402023-10-10 15:57:18.647https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdfopen.accesshttps://repositorio.uniandes.edu.coRepositorio institucional Sénecaadminrepositorio@uniandes.edu.co |