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ARTIFICIAL INTELLIGENCE-BASED IRRADIANCE AND POWER CONSUMPTION PREDICTION FOR PV INSTALLATIONS

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dc.creatorISIDORA ANTONIA CARO PEÑA
dc.creatorKARLA IVONNE LAGOS CARVAJAL
dc.creatorPABLO ALEJANDRO VALERIA AGUIRRE
dc.creatorMARÍA NATHALIE RISSO SEPÚLVEDA
dc.creatorPEDRO GERÓNIMO CAMPOS SOTO
dc.creatorFABRICIO IVÁN SALGADO DÍAZ
dc.date2022
dc.date.accessioned2025-01-10T15:30:30Z
dc.date.available2025-01-10T15:30:30Z
dc.date.issued2022
dc.description.abstractCURRENTLY, SEVERAL COUNTRIES ARE SEEKING TO CHANGE THEIR ENERGY MATRICES TOWARDS MORE SUSTAINABLE SOURCES. IN CHILE, ONE OF THE RENEWABLE SOURCES WITH INCREASED PARTICIPATION IS PHOTOVOLTAICS. HOWEVER, PHOTOVOLTAIC ENERGY SOURCES HAVE AN INTRINSIC VARIABILITY, WHICH COMBINED WITH VARIABLE DEMAND IMPOSES A CHALLENGE FOR PROPER DESIGN. CURRENTLY, TOOLS AVAILABLE FOR THE STUDY OF THIS VARIABILITY ARE EITHER COMPLEX OR EXPENSIVE. WITH THE ADVENT OF DIGITALIZATION, THERE IS AN OPPORTUNITY TO INCORPORATE TOOLS BASED ON ARTIFICIAL INTELLIGENCE TO IMPROVE FORECASTING FOR MEDIUM AND LOW POWER INSTALLATIONS. THIS WORK PRESENTS AN APPLICATION OF MACHINE LEARNING TOOLS FOR IRRADIANCE AND POWER CONSUMPTION FORECASTING. THE METHODOLOGY IS INTENDED TO BE IMPLEMENTED AS A LOW COST SOLUTION FOR SMALL SCALE GENERATION. THE RESULTS SHOW THAT IT IS POSSIBLE TO PREDICT IRRADIANCE AND ENERGY CONSUMPTION THROUGH HISTORICAL DATA, CONCLUDING THAT THE METHODOLOGY BASED ON MACHINE LEARNING IS ABLE TO SUPPORT THE DECISION MAKING FOR THE IMPROVEMENT OF PHOTOVOLTAIC SYSTEMS.
dc.formatapplication/pdf
dc.identifier.doi10.1109/CHILECON54041.2021.9702890
dc.identifier.urihttps://repositorio.ubiobio.cl/handle/123456789/12346
dc.languagespa
dc.publisher2021 IEEE CHILEAN CONFERENCE ON ELECTRICAL, ELECTRONICS ENGINEERING, INFORMATION AND COMMUNICATION TECHNOLOGIES (CHILECON)
dc.relation.uri10.1109/CHILECON54041.2021.9702890
dc.rightsPUBLICADA
dc.titleARTIFICIAL INTELLIGENCE-BASED IRRADIANCE AND POWER CONSUMPTION PREDICTION FOR PV INSTALLATIONS
dc.title.alternativeIRRADIANCIA BASADA EN INTELIGENCIA ARTIFICIAL Y PREDICCIÓN DEL CONSUMO DE ENERGÍA PARA INSTALACIONES FOTOVOLTAICAS
dc.typeARTÍCULO
dspace.entity.typePublication
ubb.EstadoPUBLICADA
ubb.Otra ReparticionDIFUSION Y PROMOCION CARRERAS
ubb.Otra ReparticionPROGRAMA DE ASISTENCIA TECNICA CON CO-FINANCIAMIENTO
ubb.Otra ReparticionDEPARTAMENTO DE INGENIERIA ELECTRICA Y ELECTRONICA
ubb.Otra ReparticionDEPARTAMENTO DE INGENIERIA ELECTRICA Y ELECTRONICA
ubb.Otra ReparticionDEPARTAMENTO DE SISTEMAS DE INFORMACION
ubb.Otra ReparticionDEPARTAMENTO DE INGENIERIA ELECTRICA Y ELECTRONICA
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ubb.SedeCONCEPCIÓN
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