SolarGIS: Online Access to High-Resolution Global Database of Direct Normal Irradiance
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1 SolarGIS: Online Access to High-Resolution Global Database of Direct Normal Irradiance Marcel Suri PhD Tomas Cebecauer, PhD GeoModel Solar Bratislava, Slovakia Conference Conference SolarPACES 2012, 13 September 2012, 2012, Marrakech, Morocco SolarPACES 13 September geomodelsolar.eu solargis.info 2012,[1]Marrakech, Morocco
2 About GeoModel Solar Development and operation of SolarGIS online system Global solar resource and meteo database Software and data services for solar energy: Prospection, site selection and prefeasibility Planning Monitoring and performance assessment Forecasting Expert consultancy and services in solar resource assessment geomodelsolar.eu solargis.info Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [2]
3 Requirements for Direct Normal Irradiance Data need to be available at any location (global coverage) They need to represent long climate record at least 10 years They need to be harmonized and without gaps High accuracy, low uncertainty (validated) High level of detail (temporal, spatial) Data products should be available: long-term averages, time series, TMY Continuity: Historical data Data for monitoring, nowcasting Data for forecasting This is available with satellite-based data, supported by high-quality ground measurements Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [3]
4 Computation scheme of SolarGIS model satellite data aerosols water vapour elevation snow temperature cloud transmittance clear-sky model conversion models Ground measurements DNI, GHI, DIF, GTI, Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [4]
5 Preconditions of the Global Solar Resource Database (1) Input data (implemented in SolarGIS) Geostationary satellites 3 km spatial resolution Frequency of meas. 15 min, 30 min, 3 hours Available globally (Meteosat, GOES, MTSAT ) Consistency, high availability History (up to 18+ years) Atmospheric and meteo databases Aerosols (ECMWF daily) Water vapour and temperature (NOAA - daily) Digital terrain model SRTM-3 (90 metres) Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [5]
6 Preconditions of the Global Solar Resource Database (2) Models - applicable worldwide SolarGIS implementation Clear-sky model atmospheric conditions Satellite model cloud attenuation Conversion models direct and diffuse Terrain disaggregation model - SOLIS (Ineichen) - Adaptation of Perez model - Dirindex, Perez diffuse model - Ruiz-Arias et al model High performance IT infrastructure Large volume of data (acquisition, processing, storage) Fast access Effective storage and management Live link to data suppliers: satellite/atmospheric and meteo data Live link to customers: near-realtime data delivery Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [6]
7 Innovation of SolarGIS Satellite data Stable radiometry over all history Stable positional and temporal accuracy Satellite model Improved albedo and cloud detection Improved snow/ice/fog detection Reduced anomalies over deserts More reliable representation of daily profiles Adaptation of clear-sky model and DNI model Very high resolution terrain (up to 90 metres) radiometric and positional preprocessing multispectral and multivariate data analysis use of daily atmospheric data Ruiz-Jarias model Fast access to the global data (between latitudes 60 degs) geomodelsolar.eu/publications Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [7]
8 SolarGIS validation: Direct Normal Irradiance Uncertainty of the estimate depends on: geography input data and models spatial and time resolution quality of validation data Only high-quality ground measurements provide correct picture of the satellite data uncertainty Hourly or more detailed data have to be used: 60 DNI sites 235 AERONET sites Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [8]
9 SolarGIS validation: Direct Normal Irradiance Model (v. 1.8) accuracy for DNI: rmbe: -1.5% rrmse hourly: 31.8% rrmse daily: 19.5% rrmse monthly: 8.2% User s uncertainty: annual values - P90 confidence: GHI 3.5% (100+ data points) DNI 7.0% (60 data points) Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [9] Uncertainty of the best ground sensors: 2% for GHI 1% for DNI
10 SolarGIS uncertainty: Direct Normal Irradiance SolarGIS high uncertainty high latitudes high mountains high and changing aerosols reflecting desert surfaces snow and ice SolarGIS low uncertainty arid and semiarid regions low and medium aerosols Hourly values Daily Monthly Yearly The uncertainty for ground sensors considers that they are well maintained, calibrated and data quality is controlled ±7 to 12% Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [10]
11 Data services Historical data (6/13/18 years) Long-term averages Time series Typical Meteorological year imaps & climdata applications Near-real time data supply Daily supply of time series Used for quality validation of DNI measurements Computer-to-computer data exchange Site-adaptation of satellite data based on correlation with ground measurements Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [11]
12 SolarGIS imaps Prefeasibility, site selection and data comparison Solar and temperature data: long-term annual and monthly averages Solar data resolution 250 metres Terrain and other global data Google search Accurate coordinates Measuring tools for distance and area Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [12]
13 SolarGIS climdata Purchase of solar and meteo data products Time series TMY Aggregated values Automatic data supply Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [13]
14 Challenges Identification of sources of uncertainty Large potential for uncertainty reduction variable Humid tropics Arid & semi-arid Temperate climate Steep terrain Snow & ice Costal zones Polluted areas Elevation, shading Clear-sky Model very low very low very low low very low very low very low very low very low very low low very low low Aerosols low high low medium low high Water vapour very low very low very low low very low very low Cloud index medium/ high low medium low medium low low Sources of DNI uncertainty Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [14]
15 Opportunities Real-time services Historical data delivery in real time Nowcasting Forecasting Grid management SolarGIS: status today for (almost) any site or portfolio of sites with uncertainty estimate Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [15]
16 Thank you! Marcel Suri Tomas Cebecauer GeoModel Solar s.r.o., Bratislava Slovakia Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [16]
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