Case study01 Energy

The Future of
Energy

Wind energy production

Advanced simulations for a climate resilient energy sector

The green transition boosts resilience to climate disruptions through renewable energy and advanced digital simulations.

How can a digital twin help the energy sector?

Predicting renewable energy production:

The advanced simulations of the digital twin enable users to explore different climate scenarios and predict renewable energy production according to the variability of climate conditions.

Enhancing grid stability and reliability:

A more accurate prediction of renewable energy production facilitates a smoother integration of renewable sources to the energy grid, enhancing grid stability and reducing the dependence on less reliable energy sources. This is key to ensure that the energy supply can meet the energy demand.

Developing strategies for climate extremes:

A digital twin allows the analysis of past extreme events to understand the conditions under which they had occurred. This allows the development of more efficient adaptation strategies in the light of the future increase in the frequency and the intensity of extreme events, offering a powerful combination of retrospective and prospective analysis.

Transforming wind to energy

The renewable energy sector is significantly impacted by climate variability and change.

Phenomena such as wind droughts, heatwaves, and droughts can both affect energy supply and demand. In the case of wind, daily variability is especially relevant, which makes high-resolution information desirable.

Digital twins are revolutionising the way to approach wind farm development and energy management.

By allowing users to perform simulations that replicate real-world conditions, digital twins can help energy practitioners to map the wind potential of different regions, optimise the location of wind turbines, and predict energy generation.

The energy output of a wind turbine depends on a variety of factors, the most important being the wind speed at the height at which the turbines are placed. Current state-of-the-art models only provide wind information at 10 metres, whereas wind turbines are normally placed at around 100 metres height, and this requires an interpolation to convert wind speed from 10 to 100 metres.

Legend: wind energy. Data source: nextGEMS

Planning decisions in the wind energy sector

Real-time access to capacity factor data:

Real-time access to capacity factor data revolutionises energy supply management, boosting memory use efficiency and enhancing the integration with climate models.

Capacity factor as a universal metric:

The capacity factor allows a safe comparison between different power plants, irrespective of their size and type, being a relevant metric for wind farm owners, operation and maintenance teams, energy traders and transmission system operators.

Impact of future climate conditions:

Exploring the changes in the capacity factor under different future climate conditions is important for making decisions at both the asset and farm levels.

Strategic importance for European energy systems:

Understanding how the capacity factor may change under different climate conditions is, more broadly, also vital for assessing the risks for the European energy systems and planning the future energy grid.

Exploring energy futures

Inside the 2018 heatwave
on the Iberian Peninsula

Why storylines for energy futures?

Storylines in climate science make climate information more relevant and understandable, aiding decision-making, especially when used with digital twin simulations.

Using storylines to simulate the 2018 heatwave under current and future conditions to understand their potential impacts.

Present-day plots represent the simulation of an event under current conditions, covering the last few decades, to ensure that the model accurately captures the event. Future scenario plots simulate the same event under different levels of global warming to explore how it might manifest in various future climates.

LOW (20º C)

HIGH (47º C)

CONTOUR LINE: +35º C

CONTOUR LINE: +42º C

LOW (20º C)

HIGH (47º C)

CONTOUR LINE: +35º C

CONTOUR LINE: +42º C

SIM. 01

7th August 2018

In the case of the 2018 heatwave, maximum temperatures were well captured in valley and mountain ridges such as the Pyrinees, while some differences in maximum temperature remained along the Portuguese western coast.

Source: Destination Earth

SIM. 02

Future scenario: +2ºC

If the same heatwave episode were to take place under a 2°C warmer climate, a larger area of the Iberian Peninsula would be experiencing extreme temperatures, with the highest values nearly hitting 49°C. Increases in maximum temperature in some areas could reach up to 5°C compared to present-day temperatures. Areas undergoing the greatest change in temperature extremes are located in the inland northwestern Iberian Peninsula, with a warming ranging between 3.5 and 5°C.