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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)

Table of Contents

General

Description

Electricity demand is computed via a statistical model using 3 climate variables as predictors: 2 m air temperature (TA), solar radiation (GHI) and Wind Speed at 10 m (WS10).

EDM defined as the daily energy (units=MWh) consumed on the grid. Electricity demand is also provided as daily mean power (units=MW). Daily mean power = daily energy / 24 (hours)

They are also provided at monthly, seasonal and annual time scale. For NRG, the aggregation is a sum, whereas for PWR, it is an average.

Individual models were built for each European country, using Generalized Additive Models (GAMs), and ERA5 data as climate inputs, as NUTS0 averages. The models are built using recent years ENSTO- E data, varying from 2006 and 2018 included depending on the country. In each case, the models were set up and validated on independent periods. The trend is estimated on the longest possible period, then fixed, so that the final product, which is the EDM reconstructed on 1979-2019, has no long-term trend, and a mean level corresponding to that of the training period. In a later stage, we may provide demand data has anomalies with respect to a reference which needs to be specified.

In any case, based on the definition above, users can define their own reference and calculate their own anomaly dataset, then any future scenario for projections.

One of the predictors of energy demand is a smoothed temperature over a period which varies depending on countries. For seasonal forecasts, this means that temperature data is necessary for the days before the start of the seasonal forecast model run. The choice has been made to use ERA5 temperature data. As ERA5-T is available with a few days delay, this means that the seasonal forecasts for demand can be run only a few days after the seasonal climate variables are available.

EDM is available for three streams:

Historical: This dataset uses climate predictors from the ERA5 reanalysis and retrieved from the CDS and averaged at NUTS0 (country). No bias adjustment has been applied.

Seasonal Forecasts: This dataset uses climate predictors from ECMWF System 5, Météo-France ARPEGE System 7 and Met Office GloSEA5 System 14. Seasonal Forecasts are retrieved from the CDS and are subsequently bias adjusted via quantile mapping. The forecast datasets are updated monthly when the raw forecast of each system is available and averaged for NUTS0 (country).

Projections: This dataset uses climate predictors 11 regional climate model (RCM)/global climate model (GCM) combinations for the EURO-CORDEX project (Table 1, Appendix) and for two Representative Concentration Pathways (RCP4.5 and RCP8.5), with RCP2.6 also added for two of the RCM/GCM combinations. Historical forcing is used from 1979-2005, and RCP forcing from 2006-2100. The original EURO-CORDEX simulations are retrieved from the producers (some were already available on the Earth System Grid Federation (ESGF) portal) and are subsequently bias adjusted by applying the Cumulative Distribution Function transform (CDFt) method. The gridded
0.25° latitude/longitude data are averaged at NUTS0 (country).

Units

Electricity demand (energy): MWh, labelled as NRG in the output files. Electricity demand (mean power): MW, labelled as PWR in the output files.

Data will eventually be available via the C3S Energy/CDS demonstrator.

Data format

NUTS0 are available as CSV files.

Keywords

Electricity Demand (EDM) Load, Power, Energy, ENTSO-E, Generalized Additive Models.

Contact

Dataset coverage

Geographic area

European countries within the C3S Energy domain is: 26.5° N to 72.5° N by 22.0° W to 45.5° E. Specifically, there 32 European countries have been considered, based on the availability of daily load data at the time of models training): AT, BA, BE, BG, CH, CZ, DE, DK, EE, EL, ES, FI, FR, HR, HU, IE, IT, LT, LU, LV, ME, MK, NL, NO, PL, PT, RO, RS, SE, SI, SK, UK. Depending on ENTSO-E and other input data availability, four additional countries might also be considered in the future: Albania (AL), Cyprus (CY), Iceland (IS) and Turkey (TR).

Temporal resolution

Daily, monthly, seasonal (DJF, MAM, JJA, SON) and annual mean power (PWR, in MW) and cumulated energy consumption (NRG, in MWh).

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 1993-2016 period for the three models used by C3S Energy: ECMWF Sys5, Météo-France Sys7 and UK MetOffice 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 have been

computed every month from the first month of availability in the current version on the CDS:



Forecast availability


ECMWF Sys5

From January 2017

MTFR Sys7

From October 2019

METO Sys14

From June 2019

Projections: 1971-2100

Spatial resolution

Data is available at NUTS0 level for the 32 countries listed above.

Lineage statement

Original data source

Energy data: ENTSO-E Power Statistics

Historical: ERA5

Seasonal Forecasts:

  1. ECMWF seasonal forecast system 5 technical description
  2. Météo-France seasonal forecast system 7 technical description
  3. Met Office

Projections: EURO-CORDEX Climate indicators (air temperature, wind speed and solar radiation) available via the Earth System Grid Federation (ESGF) portal.

Tools used in the production of indicators

R Studio Version 1.1.463 – © 2009-2018 RStudio, Inc. R version 3.6.1 (2019-07-05)
R packages (latest versions): chron, corrr, easyNCDF, fields, glue, lubridate, maptools, ncdf4, raster, readxl, rgdal, rgeos, seas, sf, shapefiles, sp, tidyverse
NCO netCDF Operators version 4.7.5: ncks

Data Quality

The EDM data reconstruction quality has been assessed for each individual country over the historical period, using ENTSO-E data.

Appendix

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


This document has been produced in the context of the Copernicus Climate Change Service (C3S).

The activities leading to these results have been contracted by the European Centre for Medium-Range Weather Forecasts, operator of C3S on behalf of the European Union (Delegation agreement signed on 11/11/2014). All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose.

The users thereof use the information at their sole risk and liability. For the avoidance of all doubt , the European Commission and the European Centre for Medium - Range Weather Forecasts have no liability in respect of this document, which is merely representing the author's view.

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