RESILIENCE: A semi-operational prototype to predict wind speed at seasonal time scales

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Type: 
Conference contribution (poster)
Organizer: 
EWEA
Event: 
EWEA 2015 annual event
Author/s: 
Christel, I., Davis, M., Doblas-Reyes, F., Torralba Fernandez, V., Gonzalez-Reviriego, N., Soret, A.
Place: 
Paris
Dates: 
Tuesday, November 17, 2015 to Friday, November 20, 2015

Introduction:

Predicting the future variability of energy resources beyond the first two weeks can allow end users to take calculated, precautionary actions with potential cost savings. Weather and its behaviour over time -known as climate- has a considerable effect on energy demand and supply and influences many decisions. Energy producers, for instance, adjust their strategies based on a foreseen energy capacity, and wind farm operators plan for optimal meteorological conditions to undertake maintenance works. The earlier these decisions can be planned, the sooner unforeseen operational risks could be identified.

Approach:

To estimate future climate variability over coming weeks or seasons, current energy practices use a deterministic approach based on retrospective climatology. Recent advances in global climate models that simulate the physics of the whole climate system, demonstrate that probabilistic forecasting can improve upon this methodology at some spatial and temporal scales.

Main body of abstract:

Probabilistic climate forecasts come with a new set of challenges for end users: information is often untailored and hard to understand and apply in a decision-making context. EUPORIAS is a collaborative project funded by the European Commission to address these challenges and support the development of climate services in Europe. One of the outcomes of this project will be RESILIENCE, a semi-operational, energy prototype of climate services that will operate on a sub-seasonal to seasonal timescale. This prototype will address the drawbacks of the probabilistic climate forecasts mentioned above to facilitate their inclusion in the habitual decision-making processes for the energy sector. State-of-the-art forecasts will be created in partnership with project SPECS, an ongoing, parallel European project that will deliver a new generation of climate forecast systems with improved forecast quality.

Conclusion:

With probabilistic climate forecasts the energy decision-makers now have a novel set of climate risk management tools that can strengthen their decision making, but are they ready to use them? The RESILIENCE prototype aims to be the tool to bring these forecasts to the energy sector in a user friendly interface.

Learning objectives:

By presenting the prototype we want all interested parties in the wind energy sector to visualize how this novel methodology could impact in their decision-making processes and ultimately encourage them to use it.

PDF link: http://www.ewea.org/annual2015/conference/allposters/PO104.pdf

About

RESILIENCE aims to strengthen the efficiency and security of wind power supply within energy networks, by providing robust information of the future variability in wind power resources based on probabilistic climate predictions.