Datasets
Reanalysis Based datasets
Below are a selection of datasets i've been involved in making while at the University of Reading. Please get in touch if you'd like to work with data like this, but these datasets aren't quite fit for your purpose - we can help! If you are interested in the methods See this paper and this paper for more details.
Future climate projections of surface weather variables, wind power, and solar power capacity factors across North-West Europe
The files contain hourly time-series of weather and energy variables which have been climate-adjusted to include the impact of climate change from five different climate model simulations, with the climate change impacts centred on the year 2035 (i.e. the mean change seen from 2020-2050). The climate-adjustment is implemented as a delta climate-change correction to observed historic weather data from the ERA5 reanalysis (which is also supplied alongside for convenience).
Hourly time series of surface meteorological variables useful for energy meteorology studies have been supplied (e.g. 2m temperature, near-surface wind speeds and surface solar irradiance), as well as heating/cooling degree-days, wind power capacity factors, and solar power capacity factors. The time series are calculated at national level across a sub-set of countries over North-West Europe, as well as for a sub-set of smaller regions over Great Britain and its surrounding seas. The locations of available wind and solar farms are used to weight wind and solar capacity factors respectively. 2020 population data is used to weight surface meteorological variables. The datasets have been produced to increase the use of meteorological data within power system modelling.
ERA5 derived time series of European aggregated surface weather variables, wind power, and solar power capacity factors: hourly data from 1950-2020,
The ERA5 reanalysis (1950-2020) has been used to calculate hourly time series of surface meteorological variables useful for energy meteorology studies, as well as degree-days, wind power, and solar power capacity factors. These are calculated at European national level, as well as for a sub-set of smaller regions over the UK and surrounding seas. The locations of wind and solar farms operational in April 2021 are used to weight wind and solar capacity factors respectively. 2020 population data is used to weight surface meteorological variables. The datasets have been produced to increase the use of meteorological data within power system modelling. .
ERA5 derived time series of European country-aggregate electricity demand, wind power generation and solar power generation (1979-2018)
The ERA5 reanalysis data (1979-2018) has been used to calculate the three-hourly country aggregated wind and solar power generation for 28 European countries based on a distribution of wind and solar farms which is considered to be representative of the current situation (2017). In addition a corresponding daily time series of nationally aggregated electricity demand is provided. The datasets have been produced to investigate the inter-annual variability of the three weather-dependent power system components. .
MERRA2 derived time series of European country-aggregate electricity demand, wind power generation and solar power generation
The MERRA2 reanalysis data (1980-2018) has been used to calculate the hourly, country aggregated wind and solar power generation for 28 European countries based on a distribution of wind and solar farms which is considered to be representative of the current situation (2017). In addition a corresponding daily time series of nationally aggregated electricity demand is provided. The data sets have been produced to investigate the inter-annual variability of the three weather-dependent power system components.
Forecast Based datasets
The dataset below is based on extended range forecasts from the ECMWF and NCEP models. See this paper for more details.
Sub-seasonal forecasts of European electricity demand, wind power and solar power generation
Sub-seasonal forecasts of daily country-level European electricity demand, wind power and solar power generation, along with the driving meteorological variables, from two sub-seasonal to seasonal prediction systems and lead times extending to 44 days. The matching ERA5-derived variables are also provided to facilitate verification analyses.