Potential users

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Within the energy industry there are multiple actors with specific requirements for climate information in different temporal scales. Manufacturers, project developers, project investors, consultants and energy trading companies are some of the types of users that already have shown their interest in seasonal to decadal prediction products and particularly in the outcomes of the RESILIENCE prototype on wind speeds. Seasonal and sub-seasonal wind speed predictions are of particular interest for energy trading companies. Thus, traders have been defined as the target users for the information provided by the prototype. Nevertheless, throughout the EUPORIAS project many other types of energy stakeholders have been involved in providing information for the development of the prototype.

To better understand the profile of a potential user of RESILIENCE and its applicability in the energy sector we present you Roland, he is not a real user but he describes many of the stakeholders that have been and are still involved in the development of the RESILIENCE prototype:

“Roland works as analyst for an energy trading company in Germany that operates worldwide. His job consists on analyzing all types of available information to predict energy demand and estimated energy production from renewable sources. To estimate wind energy production he has plenty of tools for hour-to-hour wind forecasts up to 15 days. Beyond 15 days, there was no good solution in the market for wind predictions and he had to use the retrospective wind speed climatology, assuming that the past would also represent the future. Predictions for the next season are useful for his work because, according to the estimated production of energy from wind farms, the trading firm will make a decision on how much non-renewable energy will be needed to meet demand and will buy energy commodities accordingly. RESILIENCE provides Roland with a probability forecast on wind speed for the region he wants to assess. Through the on-line visualization interface of RESILIENCE Roland sees one month in advance that next season there is an 86% of probability of having stronger wind speeds than usual for the region he is studying and only 11% probability of lower wind speeds. If indeed the wind speeds were stronger the next season the price of energy would probably decrease and some wind farms would have to be stopped. There is no certainty about that increase in the wind speeds, only a probability, but there is neither certainty in the financial products that he also has to take into account. Roland will take all the information into account, including RESILIENCE probabilistic forecasts and he will write his report.”



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.