Energy Indicators¶
The Energy Indicators application provides climate-derived metrics for the wind and solar energy sectors, translating kilometre-scale climate simulations into actionable indicators to support informed decision-making for near- to mid-term adaptation to climate change. The use case delivers standard diagnostics on resource availability, variability, and extremes, along with scientific assessment and evaluation of climate model data quality and performance.
A tabular description of the indicators is provided in the Data Portfolio page.
A technical description of how these indicators are produced is provided in the Technical Description page.
Description of operational indicators¶
The application provides multiple indicators, which are listed below. Each indicator is provided at the global scale on a latitude/longitude regular grid at the native resolution of the climate model. For certain indicators, an offshore mask of 200 km is applied, thus excluding offshore locations at distances currently deemed unviable for renewable energy installations.
Wind indicators¶
High wind events
High wind events quantify the percentage occurrence of wind speeds exceeding the turbine cut-out speed, indicating periods when turbines shut down to avoid mechanical damage. The indicator is produced operationally using a 25 m s⁻¹ cut-out threshold, which is configurable.
Low wind events
Low wind events represent the percentage occurrence of wind speeds below the turbine cut-in speed, when turbines cannot generate electricity due to insufficient wind energy. The indicator is produced operationally using a 3 m s⁻¹ cut-in threshold, which is configurable.
99th percentile 100m wind speed
Extreme wind indicator showing the 99th percentile of 100m wind speed over a configurable period of time, providing information on extreme wind conditions.
Maximum 100m wind speed
Maximum wind speed at 100m height. It is provided in monthly NetCDF files.
100m wind speed histograms
Wind speed histograms at 100m height. These represent raw wind speed distributions used to characterise wind resource availability, which is relevant for wind energy production.
Production indicators¶
Capacity factor histograms
Capacity factor represents the ratio of actual energy produced by a wind turbine to the theoretical maximum possible energy output if the turbine operated at rated power. They are operationally produced in the form of histograms for four different turbine types:
Turbine |
IEC class |
Hub height [m] |
Rated power [MW] |
Cut-in speed [m s⁻¹] |
Rated speed [m s⁻¹] |
Cut-out speed [m s⁻¹] |
|---|---|---|---|---|---|---|
Enercon E70 |
I |
85 |
2.3 |
2.0 |
15.0 |
25.0 |
Gamesa G87 |
II |
83.5 |
2.0 |
3.0 |
14.0 |
25.0 |
Vestas V110 |
III |
100 |
2.0 |
4.0 |
12.0 |
20.0 |
Vestas V164 |
S |
105 |
9.5 |
3.5 |
14.0 |
25.0 |
Solar Indicators¶
Photovoltaic potential
Photovoltaic (PV) potential, representing the available solar energy for power generation based on surface solar irradiance, 2m air temperature, and near-surface wind conditions.
Demand indicators¶
Heating degree days
Heating degree days quantify how much (in degrees) and for how long (in days) air temperature falls below a base temperature, providing a proxy for heating energy demand required to maintain indoor thermal comfort. The indicator is produced operationally using a 15.5 °C base temperature (i.e., standard for the European continent), which is configurable.
Cooling degree days
Cooling degree days measure how much (in degrees) and for how long (in days) air temperature exceeds a base temperature, providing a proxy for cooling energy demand for air conditioning and indoor thermal comfort. The indicator is produced operationally using a 22 °C base temperature (i.e., standard for the European continent), which is configurable.
Accessing the data¶
Note
Data for this application will become available on the DestinE Data Lake in a forthcoming update.
Scientific Evaluation¶
Note
Scientific evaluation for this application will be available in a forthcoming update.
Code availability and further information¶
For more information on the Energy Indicators package base code, please visit the GitHub repository.
References
Lacima-Nadolnik, A., Grayson, K., Roura-Adserias, F., Ghosh, S., Keller, K., Batlle, M., Gonzalez-Yeregi, I., Samsó-Cabré, M., Soret, A., Doblas-Reyes, F. J. (preprint). Near-term streamed climate information from kilometre-scale global climate models for the wind energy sector. Available at SSRN
Ghosh, S., Ganguly, D., Dey, S., Chowdhury, S. G. (2024). Future photovoltaic potential in India: navigating the interplay between air pollution control and climate change mitigation. Environmental Research Letters, 19(12), 124030. Available at https://doi.org/10.1088/1748-9326/ad8c68
Contact the developers¶
Contact the developers at energy-destine@bsc.es