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Overview of Solar Energy in Brazil Overview of Solar Energy in Brazil 1st Workshop Solar Energy, FAPESP 13/11/2017 Enio Bueno Pereira [email protected] LABREN - Laboratory for Modelling and Studies of Renewable Energy Resources INPE – National Institute for Space Research Brazil’s NDC Nationally Determined Contributions Brazil’s Commitment to the Paris Agreement Greenhouse gas emissions Waist Industrial Treatment 2005 Processes 3% 5% Energy Generation Land Use 24% -37% and Forests 2015 46% Agriculture 2030 22% 14/11/2017 1st Workshop Solar Energy - FAPESP Brazil’s electricity energy matrix dispatch of thermoelectric plants nuclear photovoltaic 14% 39000 wind 1,2% 0,02% 6,5% thermal 12% 37000 26% 10% 35000 8% Thermal/Hydro Hydro / GWh 33000 6% GWh 31000 4% Thermal water crisis Source ANEEL 2017 29000 hydro 2% 66% 0% 27000 2010 2011 2012 2013 2014 2015 2016 2017 Source: ONS 2017 Wind and photovoltaic may be the answer to achieve the NDC goal for non- hydro renewable energy generation along with biomass 14/11/2017 1st Workshop Solar Energy - FAPESP Solar irradiance in Brazil 14/11/2017 1st Workshop Solar Energy - FAPESP Information barrier • Variables energy source • Energy planning and investments demand secure science-based information to assure the return of their investments and to obtain financing for their projects • Stakeholders are interested in the knowledge of the influence of climate variability on • solar resource; • solar variability and trends; • Hydro-solar-wind complementarity, etc. 14/11/2017 1st Workshop Solar Energy - FAPESP New science sector: Energy Metorology LABREN - Laboratory for Modelling and Studies of Renewable Energy Resources http://labren.ccst.inpe.br The multidisciplinary laboratory LABREN-CCST-INPE, carries out research and teaching activities in energy meteorology and in the climate system influence on energy resources making use of satellite data, computational modelling and observational data. Research Topics: • Assessment of solar and wind energy resources • Short and medium-term forecast of solar and wind generation • Energy and global climatic changes • Site-specific measurements, characterization and modelling of solar and wind resources 14/11/2017 1st Workshop Solar Energy - FAPESP Solar resource assessment Large areas – available information • Most of the available information sources for Brazilian territory are State Governments initiatives through bidding contracts • Available information are based on statistical interpolation of ground observations 14/11/2017 1st Workshop Solar Energy - FAPESP Ground data versus model data 70 Interpola on 60 Extraplola on 50 40 30 Interpolation error (%) Interpolation 20 10 Break-even (20 – 40 km) 0 0 100 200 300 400 500 600 700 800 Distance between stations (km) New Brazilian Atlas of Solar Energy - 2007 An INPE accomplishment in association with several national universities • 17 years of satellite data • Spectral radiation transfer model • Validation by using more than 500 ground sites • National coverage Download pdf and shape format data at: 2006 http://labren.ccst.inpe.br/atlas_2017.html 14/11/2017 1st Workshop Solar Energy - FAPESP Site-specific solar assessment Model development Feasibility of projects Due- diligence • Ground measurements • Public solarimetric stations and/or networks • Site-specific from projects - proprietary data 14/11/2017 1st Workshop Solar Energy - FAPESP SONDA network http://sonda.ccst.inpe.br/ A BSRN/WMO associate Data acquisition sites managed by LABREN • INMET network Estação Tipo UF Altitude (m) Belo Jardim A PE 718 http://www.inmet.gov.br/ Brasília SA DF 1023 Cachoeira Paulista S SP 574 Caicó S RN 176 Campo Grande S MS 677 Data acquisition sites managed Cuiabá S MT 185 by partners and collaborators Ourinhos SA SP 446 Estação Tipo UF Altitude (m) Palmas S TO 216 Chapecó S SC 700 Petrolina SA PE 387 Rolim de Moura S RO 252 Curitiba S PR 891 São Luiz S MA 40 Florianópolis S SC 31 São João do Cariri A PB 486 Joinville S SC 48 São Martinho da SA RS 489 Serra Natal S RN 58 Triunfo A PE 1123 Sombrio S SC 15 14/11/2017 1st Workshop Solar Energy - FAPESP PV yield (kWh/kWp) Global latitude tilted irradiation 14/11/2017 1st Workshop Solar Energy - FAPESP 14/11/2017 tilted irradiation tilted latitude Global 1st Workshop Solar Energy Energy Solar 1st Workshop - FAPESP r a l o S a i g r e n E e d o r i e l i s a r B s a l t A 45 Model Uncertainties (mean daily totals for global horizontal irradiation) Maximum percentage deviation between modeled and observed monthly average of daily global irradiation for the percentiles of 10% and 90% 14/11/2017 1st Workshop Solar Energy - FAPESP Model Uncertainties (daily totals of global horizontal irradiation) 14/11/2017 1st Workshop Solar Energy - FAPESP Model Validation (mean daily totals for global horizontal irradiation) Good agreement of distribution curves between observed and modelled values 14/11/2017 1st Workshop Solar Energy - FAPESP Space variability daily totals of global horizontal irradiation The 25 percentile values of global solar irradiation, i.e. 75 % of the days present daily totals of global horizontal solar irradiation above these values. r a l o S a i g r e n E e d o r i e l i s a r B s a l t A 14/11/2017 1st Workshop Solar Energy - FAPESP Figura 41. Mapa do percentil P25 da irradiação global horizontal anual para o território brasileiro. 55 Annual Variability daily totals of global horizontal irradiation (kWh/m2.dia) 14/11/2017 1st Workshop Solar Energy - FAPESP Seasonal Variability daily totals of global horizontal irradiation (kWh/m2.dia) maximum mean median minimum 14/11/2017 1st Workshop Solar Energy - FAPESP Trends (mean daily totals for global horizontal irradiation) Mann-Kendall trend analysis at 95% confidence level 14/11/2017 1st Workshop Solar Energy - FAPESP maximum mean median (Brazilian regions versus Europe) Comparison minimum .dia 2 /m kWw 14/11/2017 1st Workshop Solar Energy - FAPESP Solar Hot-Water (standard sized system) Para a criação de qalqer cenário econômico é necessário partir de parâmetros como csto do eqipamento, csto da energia axiliar, taxas diversas, inflação, etc. Esses valores, porém, variam mito ao longo dos anos, levando à imprecisão das estimativas feitas. Por isso, opto‐se por aprYearlyesenta rspecific m cen thermalário de d eenergysempe nproductionho de m s i-stkWht/mema típic2o no Brasil. Considero‐se o so de: - Standard systems in North and Northeast became •coletor de placa plana com cobertra de vidro (crva oversizedde eficiênc andia co nsaturatesforme Ma thethn thermaler et al., 2 0energy15); production because of the absence of demand. •volme do reservatório igal ao volme de ága - Higher thermal energy production causes higher consmido diariamente; money savings in South and Southeast. •relação entre volme do reservatório e área de placa 75 litros/m2; •consmo diário de 300 litros de ága aqecida a 40°C; •a temperatra da ága fria eqivale à média mensal da temperatra ambiente local. Calclando a prodção anal de energia em relação à área de coletores obtém‐se m parâmetro qe pode ser facilmente r a l transformado em resltado financeiro, considerando o preço de o S specific thermal energy production a m sistema completo e a tarifa local de energia. Os resltados Figura 46. Produção anual de energia térmica por área de coletor i 14/11/2017 1st Workshop Solar Energy - FAPESP g obtidos consideram o so de m sistema padrão para todo o país solar instalada utilizando um sistema de referência (reservatório r e = consumo diário = 300 litros; relação reservatório/área de placa n e, portanto, melhores resltados podem ser obtidos analisando E 2 individalmente cada região. A Figra 46 mostra qe ma maior = 75 litros/m ; temperatura de consumo = 40°C). e d o prodção anal de energia térmica por área de coletor instalada r i e l não está necessariamente nas regiões de maior incidência de i s a irradiação solar. Isso ocorre porqe a demanda de energia térmica r B é maior em regiões de clima mais frio (Figra 47), fazendo com qe s a l o potencial de aqecimento do sistema seja melhor aproveitado. t Para as regiões de clima mais qente, o sistema adotado nessa A simlação fica sperdimensionado, pois é capaz de fornecer mais energia térmica do qe necessária. Isso também comprova a necessidade de dimensionar o eqipamento de acordo com as características climáticas locais. Nas regiões Sdeste e Sl, a maior demanda de energia exige eqipamentos maiores, o qe faz com qe os cstos específicos dos componentes complementares do sistema sejam menores, trazendo maior retorno financeiro a essas regiões. Por otro lado, o correto dimensionamento em climas mais qentes permite ma redção de csto qe pode tornar atraente economicamente sistemas de aqecimento solar, principalmente os de grande porte. É interessante também observar o menor desempenho dos eqipamentos na região Norte provocado pela alta neblosidade. Obviamente, toda essa discssão é afetada pelos preços cobrados pela energia elétrica, qe é diferente de acordo com a concessionária prestadora do serviço e ajstado analmente pelo agente reglador de acordo com os PRORET ‐ Procedimentos de Reglação Tarifária (ANEEL, 2011). 59 Potential for CSP (kWh/m2.year) 14/11/2017 1st Workshop Solar Energy - FAPESP Fast growing PV Distributed Generation Market Source: ANEEL/ABSOLAR, 2017. Last update: 01/11/2017. 14/11/2017 1st Workshop Solar Energy - FAPESP PV distribute market • 8114 residential Source: Instituto IDEAL, 2017 • 1541 commercial • 213 industrial Number of companies in the PV sector 14/11/2017 1st Workshop Solar Energy - FAPESP Installed Capacity of Distributed PV Installations by Consumption Type Source: ANEEL/ABSOLAR, 2017. Last update: 01/11/2017. 14/11/2017 1st Workshop Solar Energy - FAPESP Prices R$/Wp of distributed PV in 2016 kWp 3.81R$ = 1€ 14/11/2017 1st Workshop Solar Energy - FAPESP Large-Scale PV Power Plants in Electricity Auctions Source: CCEE/ABSOLAR, 2017.
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