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Article Dans Une Revue IEEE Transactions on Sustainable Energy Année : 2022

Special Section on Advances in Renewable Energy Forecasting: Predictability, Business Models and Applications in the Power Industry

Ricardo Bessa
Pierre Pinson
Dipti Srinivasan
Charlie Smith
Nima Amjady
Hamidreza Zareipour

Résumé

The papers in this special section focus on advances in renewable energy forecasting, predictability, business models, and applications in the power industry. During the last 25 years, research has been conducted for developing renewable energy source (RES) forecasting algorithms, especially for wind and solar energy, seeking an improvement of predictability and uncertainty forecasting products. Research on wave energy forecasting is also being conducted, although this technology is not at the same maturity levels of wind and solar energy technologies. Furthermore, the number of companies selling forecasting services has proliferated and the reliability and availability of the services have improved. Currently, power system operators and electrical energy traders use weather and power forecasts embedded in their decision-making processes. Despite all this research and adoption by the energy industry, deterministic forecasts are still predominant in utility practice mainly due to: i) lack of understanding and standardization of uncertainty forecast products; and ii) high computational time associated with stochastic and robust optimization approaches. Moreover, proven business cases are also needed to demonstrate the benefits of uncertainty forecasts to end-users.

Dates et versions

hal-04075713 , version 1 (20-04-2023)

Identifiants

Citer

Ricardo Bessa, Pierre Pinson, George Kariniotakis, Dipti Srinivasan, Charlie Smith, et al.. Special Section on Advances in Renewable Energy Forecasting: Predictability, Business Models and Applications in the Power Industry. IEEE Transactions on Sustainable Energy , 2022, 13 (2), pp.1166-1168. ⟨10.1109/TSTE.2022.3157009⟩. ⟨hal-04075713⟩
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