Estimativa da produção de energia solar fotovoltaica com base em modelos meteorológicos
Autor(a) principal: | |
---|---|
Data de Publicação: | 2018 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional Manancial UFSM |
Texto Completo: | http://repositorio.ufsm.br/handle/1/16151 |
Resumo: | Photovoltaic energy had an exponential growth in the last few years in Brazil and soon it should become an important source of energy in the Brazilian electrical system. Unlike other sources, it is not possible to control the amount of energy generated by a photovoltaic system, since the irradiance has intermittent characteristics and seasonalities. So it requires good planning of the electrical system with estimations of production in various horizons, ranging from hours to years. Irradiance predictions are very important in this planning, and one of the main tools for forecasting it are the mesoescale numerical weather prediction models. The main model of this type, Weather Research and Forecasting Model (WRF), has been the subject of studies and optimizations aiming irradiance predictions. By the predictions of irradiânce and temperature it is possible to estimate the energy production by a photovoltaic system. This work involved the creation of several tools for a possible operationalization of an irradiance forecasting system. The tools automate several operations like retrieving data from ground stations and GSF and automatic runs of the WRF model. In addition, tests were carried out to verify the influence of proper parameterizations for irradiance predictions and different aerosol configurations in the WRF. The simulations were performed for the state of Rio Grande do Sul in the period of 20 days between March 12 and March 31 of 2018. The validation of the irradiance predictions used as reference sites of INMET. The WRF runs used as a boundary condition data from the Global Forecast System (GFS). Simulations were carried out with five sets of parameterizations, one with typical parameters and four with recommended parameters for irradiance predictions. Among the simulations with parametrizations specific to irradiance predictions were simulations disconsidering aerosols, using climatological aerosols, using ECMWF-CAMS aerosols and ECMWF-CAMS aerosols plus stochastic disturbances. Generation models were also created based on the WRF using the SAPM model for the distribution facilities of the domain of the irradiance forecast. The results showed that the specific parameterizations for irradiance predictions gave better results than typical parameterizations and the use of external aerosols and perturbations led to a small decrease of the error. WRF runs with irradiance prediction parameters were more accurate than GFS on days with little cloud coverage but performed worse on days with higher sky coverage. The power generation forecsts showed that the output power of the combined photovoltaic installations of the domain formed smooth curves without presenting significant oscillations in the energy production in the intervals of 30 min of the simulations. |
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2019-04-11T13:17:33Z2019-04-11T13:17:33Z2018-08-23http://repositorio.ufsm.br/handle/1/16151Photovoltaic energy had an exponential growth in the last few years in Brazil and soon it should become an important source of energy in the Brazilian electrical system. Unlike other sources, it is not possible to control the amount of energy generated by a photovoltaic system, since the irradiance has intermittent characteristics and seasonalities. So it requires good planning of the electrical system with estimations of production in various horizons, ranging from hours to years. Irradiance predictions are very important in this planning, and one of the main tools for forecasting it are the mesoescale numerical weather prediction models. The main model of this type, Weather Research and Forecasting Model (WRF), has been the subject of studies and optimizations aiming irradiance predictions. By the predictions of irradiânce and temperature it is possible to estimate the energy production by a photovoltaic system. This work involved the creation of several tools for a possible operationalization of an irradiance forecasting system. The tools automate several operations like retrieving data from ground stations and GSF and automatic runs of the WRF model. In addition, tests were carried out to verify the influence of proper parameterizations for irradiance predictions and different aerosol configurations in the WRF. The simulations were performed for the state of Rio Grande do Sul in the period of 20 days between March 12 and March 31 of 2018. The validation of the irradiance predictions used as reference sites of INMET. The WRF runs used as a boundary condition data from the Global Forecast System (GFS). Simulations were carried out with five sets of parameterizations, one with typical parameters and four with recommended parameters for irradiance predictions. Among the simulations with parametrizations specific to irradiance predictions were simulations disconsidering aerosols, using climatological aerosols, using ECMWF-CAMS aerosols and ECMWF-CAMS aerosols plus stochastic disturbances. Generation models were also created based on the WRF using the SAPM model for the distribution facilities of the domain of the irradiance forecast. The results showed that the specific parameterizations for irradiance predictions gave better results than typical parameterizations and the use of external aerosols and perturbations led to a small decrease of the error. WRF runs with irradiance prediction parameters were more accurate than GFS on days with little cloud coverage but performed worse on days with higher sky coverage. The power generation forecsts showed that the output power of the combined photovoltaic installations of the domain formed smooth curves without presenting significant oscillations in the energy production in the intervals of 30 min of the simulations.A energia fotovoltaica tem apresentado um crescimento exponencial nos últimos anos no Brasil e em pouco tempo deve se tornar uma fonte importante de energia no sistema elétrico brasileiro. Diferentemente de outras fontes, não é possível controlar a quantidade de energia gerada por um sistema fotovoltaico, já que a irradiância tem características intermitentes e sazonalidades. Para contornar esse problema é preciso um bom planejamento do sistema elétrico com estimativas de produção em vários horizontes, que vão de horas até anos. Previsões de irradiância são muito importantes para auxiliar este planejamento, e uma das principais ferramentas para a previsão são os modelos numéricos de previsão de tempo. O principal modelo deste tipo, Weather Research and Forecasting Model (WRF), tem sido objeto de estudos e otimizações com foco específico em previsões de irradiância. Por meio das previsões da irradiância e temperatura é possível estimar a produção de energia por um sistema fotovoltaico. Este trabalho envolveu a criação diversas ferramentas para uma possível operacionalização de um sistema de previsão de irradiância e produção de energia elétrica, que envolveu desde a obtenção de dados de estações em solo, rodada automática do modelo WRF e previsão de geração para as unidades de geração distribuída. Além disso foram realizados ensaios a fim de verificar a influência de parametrizações próprias para previsões de irradiância e diferentes configurações de aerossóis no WRF. As simulações foram realizadas para o estado do Rio Grande do Sul no período de 20 dias entre 12 e 31 de março de 2018. A validação dos dados de irradiância utilizou como referência estações da rede do INMET. As rodadas do WRF utilizaram como condição de contorno dados do modelo global Global Forecast System (GFS). Foram realizadas simulações com cinco conjuntos de parametrizações, uma com parâmetros típicos e quatro com parâmetros recomendados para previsões de irradiância. Entre as simulações específicas para previsões de irradiância foram feitas rodadas sem consideração de aerossóis, com uso de aerossóis climatológicos e com aerossóis do ECMWF-CAMS com e sem perturbações estocásticas. Posteriormente foram criadas previsões de geração com base nas previsões do WRF utilizando-se o modelo SAPM para as instalações de geração distribuída do domínio da previsão de irradiância. Os resultados mostraram que as parametrizações específicas para previsões de irradiância mostraram melhor resultado que parametrizações típicas. Adicionalmente observou-se que o uso de aerossóis externos e perturbações estocásticas resultaram em reduções pouco significativas do erro. As previsões de geração mostraram que a potência de saída das instalações fotovoltaicas do domínio somadas formaram curvas suaves não apresentando oscilações significativas na produção de energia nos intervalos de 30 min das simulações.porUniversidade Federal de Santa MariaCentro de TecnologiaPrograma de Pós-Graduação em Engenharia ElétricaUFSMBrasilEngenharia ElétricaAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessPrevisão de irradiânciaFotovoltaicaWRFIrradiance forecastPhotovoltaic energyCNPQ::ENGENHARIAS::ENGENHARIA ELETRICAEstimativa da produção de energia solar fotovoltaica com base em modelos meteorológicosPhotovoltaic solar energy production estimations based in meteorological modelsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisMichels, Leandrohttp://lattes.cnpq.br/9232567042677107Zimermann, Hans Rogériohttp://lattes.cnpq.br/6886593430683676Pereira, Enio Buenohttp://lattes.cnpq.br/0638551133292550Sperandio, Mauriciohttp://lattes.cnpq.br/8051956713222836http://lattes.cnpq.br/4764063623395099Sehnem, Josue Miguel3004000000076007ad1774a-99ab-4c2c-ac49-2ac5efe7ffab9fdfcd05-c583-4fb7-8337-942d8d4eb36ed63ab6cc-aaac-4734-90ad-70888718726a2c5a136d-6b44-4692-8d87-f37f4bfb726d6e3a04c6-f7b7-4168-a2a1-8d015314dd3freponame:Repositório Institucional Manancial UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMORIGINALDIS_PPGEE_2018_SEHNEM_JOSUE.pdfDIS_PPGEE_2018_SEHNEM_JOSUE.pdfDissertação de Mestradoapplication/pdf4096566http://repositorio.ufsm.br/bitstream/1/16151/1/DIS_PPGEE_2018_SEHNEM_JOSUE.pdfe1638eabc33f8730931892b910001538MD51LICENSElicense.txtlicense.txttext/plain; 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dc.title.por.fl_str_mv |
Estimativa da produção de energia solar fotovoltaica com base em modelos meteorológicos |
dc.title.alternative.eng.fl_str_mv |
Photovoltaic solar energy production estimations based in meteorological models |
title |
Estimativa da produção de energia solar fotovoltaica com base em modelos meteorológicos |
spellingShingle |
Estimativa da produção de energia solar fotovoltaica com base em modelos meteorológicos Sehnem, Josue Miguel Previsão de irradiância Fotovoltaica WRF Irradiance forecast Photovoltaic energy CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA |
title_short |
Estimativa da produção de energia solar fotovoltaica com base em modelos meteorológicos |
title_full |
Estimativa da produção de energia solar fotovoltaica com base em modelos meteorológicos |
title_fullStr |
Estimativa da produção de energia solar fotovoltaica com base em modelos meteorológicos |
title_full_unstemmed |
Estimativa da produção de energia solar fotovoltaica com base em modelos meteorológicos |
title_sort |
Estimativa da produção de energia solar fotovoltaica com base em modelos meteorológicos |
author |
Sehnem, Josue Miguel |
author_facet |
Sehnem, Josue Miguel |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Michels, Leandro |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/9232567042677107 |
dc.contributor.advisor-co1.fl_str_mv |
Zimermann, Hans Rogério |
dc.contributor.advisor-co1Lattes.fl_str_mv |
http://lattes.cnpq.br/6886593430683676 |
dc.contributor.referee1.fl_str_mv |
Pereira, Enio Bueno |
dc.contributor.referee1Lattes.fl_str_mv |
http://lattes.cnpq.br/0638551133292550 |
dc.contributor.referee2.fl_str_mv |
Sperandio, Mauricio |
dc.contributor.referee2Lattes.fl_str_mv |
http://lattes.cnpq.br/8051956713222836 |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/4764063623395099 |
dc.contributor.author.fl_str_mv |
Sehnem, Josue Miguel |
contributor_str_mv |
Michels, Leandro Zimermann, Hans Rogério Pereira, Enio Bueno Sperandio, Mauricio |
dc.subject.por.fl_str_mv |
Previsão de irradiância Fotovoltaica WRF |
topic |
Previsão de irradiância Fotovoltaica WRF Irradiance forecast Photovoltaic energy CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA |
dc.subject.eng.fl_str_mv |
Irradiance forecast Photovoltaic energy |
dc.subject.cnpq.fl_str_mv |
CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA |
description |
Photovoltaic energy had an exponential growth in the last few years in Brazil and soon it should become an important source of energy in the Brazilian electrical system. Unlike other sources, it is not possible to control the amount of energy generated by a photovoltaic system, since the irradiance has intermittent characteristics and seasonalities. So it requires good planning of the electrical system with estimations of production in various horizons, ranging from hours to years. Irradiance predictions are very important in this planning, and one of the main tools for forecasting it are the mesoescale numerical weather prediction models. The main model of this type, Weather Research and Forecasting Model (WRF), has been the subject of studies and optimizations aiming irradiance predictions. By the predictions of irradiânce and temperature it is possible to estimate the energy production by a photovoltaic system. This work involved the creation of several tools for a possible operationalization of an irradiance forecasting system. The tools automate several operations like retrieving data from ground stations and GSF and automatic runs of the WRF model. In addition, tests were carried out to verify the influence of proper parameterizations for irradiance predictions and different aerosol configurations in the WRF. The simulations were performed for the state of Rio Grande do Sul in the period of 20 days between March 12 and March 31 of 2018. The validation of the irradiance predictions used as reference sites of INMET. The WRF runs used as a boundary condition data from the Global Forecast System (GFS). Simulations were carried out with five sets of parameterizations, one with typical parameters and four with recommended parameters for irradiance predictions. Among the simulations with parametrizations specific to irradiance predictions were simulations disconsidering aerosols, using climatological aerosols, using ECMWF-CAMS aerosols and ECMWF-CAMS aerosols plus stochastic disturbances. Generation models were also created based on the WRF using the SAPM model for the distribution facilities of the domain of the irradiance forecast. The results showed that the specific parameterizations for irradiance predictions gave better results than typical parameterizations and the use of external aerosols and perturbations led to a small decrease of the error. WRF runs with irradiance prediction parameters were more accurate than GFS on days with little cloud coverage but performed worse on days with higher sky coverage. The power generation forecsts showed that the output power of the combined photovoltaic installations of the domain formed smooth curves without presenting significant oscillations in the energy production in the intervals of 30 min of the simulations. |
publishDate |
2018 |
dc.date.issued.fl_str_mv |
2018-08-23 |
dc.date.accessioned.fl_str_mv |
2019-04-11T13:17:33Z |
dc.date.available.fl_str_mv |
2019-04-11T13:17:33Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/masterThesis |
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masterThesis |
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http://repositorio.ufsm.br/handle/1/16151 |
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http://repositorio.ufsm.br/handle/1/16151 |
dc.language.iso.fl_str_mv |
por |
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por |
dc.relation.cnpq.fl_str_mv |
300400000007 |
dc.relation.confidence.fl_str_mv |
600 |
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dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Centro de Tecnologia |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Engenharia Elétrica |
dc.publisher.initials.fl_str_mv |
UFSM |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Engenharia Elétrica |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Centro de Tecnologia |
dc.source.none.fl_str_mv |
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