Contributors: A. Troccoli (WEMC), L. Sanger (WEMC), C. Goodess (WEMC), J. Ogonji (WEMC), L. Dubus (WEMC), R. Vautard F Pons (CEA), X. Jin (CEA), G. Levavasseur (CEA), R. Legrand (MF), L. Grigis (MF), S. Martinoni-Lapierre (MF), C. Viel (MF), S. Parey (EDF), B. Oueslati (EDF), Y-M. Saint-Drenan (ASSOCIATION POUR LA RECHERCHE ET LE DEVELOPPEMENT DES METHODES ET PROCESSUS INDUSTRIELS, ARMINES, FRANCE), J. Mendes (MO), J. Osborne (MO), G.Guentchev (MO)
1. General
1.1. Description
Datasets of Solar PhotoVoltaic Power (SPV) are computed through a mix of physical and statistical model. SPV capacity factor (CFR) is defined as the ratio of actual generation over installed capacity (sum of the peak capacity of all PV systems installed in the region of interest). The solar PV capacity factor is calculated at grid point level. It is important to highlight that this quantity does not represent the power production of a single PV system. Instead, it is designed to represent the aggregated production of the PV plant installed in each pixel. For this purpose, the power production of a PV system is calculated from the meteorological data (GHI and 2 m temperature) for different module orientations taking a reference PV plant model and using empirical models of the main parts of a PV system (optical losses, module, inverter). These different power values are then aggregated assuming a distribution of the different module orientations for the considered location. The distribution of module orientation is dependent on the location via the optimal tilt angle using a parameterization developed in the C3S ECEM contract.
SPV is available for three streams:
Historical: This dataset is based on the ERA5 (for GHI and 2 m air temperature) at 0.25° resolution. Averages for NUTS0 (country) and NUTS2 (sub-country) areas are also available. |
Seasonal Forecasts: This dataset is currently available for ECMWF System 5, Météo-France ARPEGE System 7 and MetOffice GloSEA5 System 14. Seasonal Forecasts are retrieved from the CDS and are subsequently bias adjusted via quantile mapping. The forecast datasets, 1° resolution, are updated monthly when the raw forecast of each system is available. Averages for NUTS0 (country) are also provided. |
Projections: This dataset is available for eleven regional climate model (RCM)/global climate model (GCM) combinations for the EURO-CORDEX project (Table 1) and for two Representative Concentration Pathways (RCP4.5 and RCP8.5). Historical forcing is used from 1979-2005, and RCP forcing from 2006-2100. The original EURO-CORDEX simulations of the needed input variables are retrieved from the producers and are subsequently bias adjusted by applying the Cumulative Distribution Function transform (CDFt) method. Further processing involved interpolation to a standard 0.25° latitude/longitude grid, and averages for NUTS0 (country) and NUTS2 (sub-country) |
1.2. Units
SPV as capacity factor: unitless, labelled as CFR in the output files. SPV as energy: MWh, labelled as NRG in the output files.
SPV as mean power: MW, labelled as PWR in the output files.
1.3. Links
Data will eventually be available via the C3S Energy/CDS demonstrator.
1.4. Data format
Gridded data (0.25° for HIST and PROJ, 1° for SEAS): NetCDF
NUTS0, NUTS2, MAR0 and MAR1 averages: CSV
1.5. Keywords
Solar PhotoVoltaic Power (SPV).
PV power, regional PV, Capacity Factor, Power, Energy, solar.
1.6. Contact
Please raise a ticket through the ECMWF Support Portal (ECMWF login required).
2. Dataset coverage
2.1. Geographic area
C3S Energy domain is: 26.5° N to 72.5° N by 22.0° W to 45.5° E.
2.2. Temporal resolution
Historical: 1-hour time step as accumulated value. Averages for daily, monthly, seasonal (DJF, MAM, JJA, SON) and annual are also computed for NUTS0 and NUTS2 mean values. |
Seasonal Forecasts: 24-hour time step as accumulated value (gridded data). Averages for monthly, seasonal (DJF, MAM, JJA, SON) and annual are also computed for NUTS0 mean values. |
Projections: 3-hour time step as accumulated value (gridded data). Daily NUTS0 and NUTS2 averages are also computed. |
2.3. Time period
Historical: 1979 to present (ca. 1 month behind real time); updated every month based on ERA5T data availability. | ||||
Seasonal Forecasts: The hindcasts cover the period 1993-2016 for the three models used by C3S Energy: ECMWF Sys5, Météo-France Sys7 and UK Met Office Sys14. ECMWF has all the month, MTFR SY07 currently covers October to April with the rest of the months to be completed by mid- May 2020 as this is a new system. METO SY14 ranges from June to April (notice that METO SY14 is a rolling release model, hindcast have to be computed each months). The forecasts updated have been run every month from the first month of availability in the current version on the CDS: | ||||
Forecast availability | Forecast horizon | |||
ECMWF Sys5 | From January 2017 | 215 days (24-hourly time steps) | ||
MTFR Sys7 | From October 2019 | 211 days (24-hourly time steps) | ||
METO Sys14 | From June 2019 | 215 days (24-hourly time steps) | ||
Projections: 1980 to 2098 (common period), with historical forcing to 2005, then RCP forcing. | ||||
2.4. Spatial resolution
Historical: 0.25° by 0.25° latitude/longitude. Data are also available as averages for more than 30 European countries (NUTS0) and ca. 350 NUTS2 areas. |
Seasonal Forecasts: 1° by 1° latitude/longitude. The underlying forecast systems run at different resolutions. Data are also available as averages for more than 30 European countries as NUTS0 areas. |
Projections: 0.25° by 0.25° latitude/longitude. Data are also available as averages for more than 30 European countries (NUTS0) and ca. 350 NUTS2 areas. |
3. Usage
3.1. Citation(s)
Saint-Drenan YM, Wald L, Ranchin T, Dubus L, Troccoli A (2018) An approach for the estimation of the aggregated photovoltaic power generated in several European countries from meteorological data. Advances in Science and Research, 15, 51-62, available here.
4. Lineage statement
4.1. Original data source
- Energy data: the parameter dataset used in the SPV model is taken from the optimal tilt angle disseminated by PV-GIS; ENTSO-E Power Statistics
Historical: ERA5 for climate indicators (solar radiation and air temperature) |
Seasonal Forecasts: i. ECMWF seasonal forecast system 5 technical description ii. Météo-France seasonal forecast system 7 technical description iii. Met Office |
Projections: EURO-CORDEX Climate indicators (solar radiation and air temperature) available via the Earth System Grid Federation (ESGF) portal. |
4.2. Tools used in the production of indicators
Python 3.1 and the following libraries: Pandas, Datetime, Pvlib, numpy
5. Data Quality
The algorithm used to generate the data has been evaluated in detail against ENTSO-E data using ERA-interim data. The result of this validation can be found in Saint-Drenan et al. (2018). The accuracy of the data generated with ERA5 has been evaluated. A more detailed evaluation of the historical SPV data using the latest ENTSO-E data is in progress.
Table 1: List of the 11 EURO-CORDEX simulations and the institutes that provided the data.
Short name | Driving GCM | RCM | Contact Institute | Period |
HIIC | ECEARTH | HIRAM | Danish Meteorological Institute (DMI) | 1951 - 2100 |
RAIC | ECEARTH | RACMO | Royal Netherlands National Meteorological Institute (KNMI) | 1950 - 2100 |
RCIC | ECEARTH | RCA | Swedish Meteorological and Hydrological Institute (SMHI) | 1970 - 2100 |
RAMO | HADGEM | RACMO | KNMI | 1951 - 2098 |
RCMO | HADGEM | RCA | SMHI | 1970 - 2098 |
ReMO | HADGEM | REGCM | International Centre for Theoretical Physics (ICTP) | 1971 - 2099 |
WRIP | IPSL | WRF 381P | Institute Pierre Simon Laplace (IPSL) | 1951 - 2100 |
RCMP | MPI | RCA | SMHI | 1970 - 2100 |
CCMP | MPI | CCLM | Climate Limited-area Modelling Community | 1950 - 2100 |
HINC | NORESM | HIRAM | Danish Meteorological Institute (DMI) | 1951 - 2100 |
ALCN | CNRM | ALADIN63 | CNRM (Centre National de Recherches Meteorologiques, Toulouse 31057, France) | 1952 - 2100 |
