Firstly, a collaboration on the improvement of the scientific basis for the wind predictions themselves. This includes numerical weather prediction model physics, but also widely distributed information on accessible datasets. Secondly, we will be aiming at an international pre-standard (an IEA Recommended Practice) on benchmarking and comparing wind power forecasts, including probabilistic forecasts. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions.
This WP will bring together global leaders in NWP models as applied to the wind industry to exchange information and recommendations regarding most promising areas to improve both the physics of these models and data assimilation methods, and the influence of various data types, such as data from drones, masts, lidars and turbines in data-sparse areas, e.g. offshore for wind energy forecasting.
The emphasis will be on improvements of the wind-related forecast performance of these models especially in typical rotor heights. There, the effects of changing stability, complex terrain, the influence of the surface and phenomena such as low-level jets still are only poorly modeled. Forecasting time horizons of 0-3 hours, 3-12 hours, day ahead, 2 weeks ahead, and seasonal are the relevant time scales for the power system, and will be the focus of separate investigations. This can include artificial intelligence techniques or Rapid Update Cycles.
This second work package will review the state-of-the-art for error and uncertainty quantification for wind and wind power forecasting models, with a special emphasis on the underlying NWP forecasts. This activity will further engage both NWP and field measurement researchers to develop guidelines, best practices, and perhaps standards, for evaluating forecast uncertainties. For model evaluation, we would work together with Task 31 in their Model Evaluation Protocol (MEP) implemented in the WindBench platform. This would include trying to use some of their collected datasets while also opening a call for additional datasets for benchmarking.
In this work package (WP3) we will survey the current state of use of forecasting solutions by the power systems sector and develop general recommendations for:
- How to select the right methodology for a given forecasting task
- The value and application of probabilistic forecasting solutions in the real-time environments
- Requirements of measurement data for grid codes in real-time forecasting
The objective of this wok package is to engage both actors of the wind industry and the research communities to identify how current and emerging capabilities to determine forecast methodologies that can be used to address the variety of decision-support needs of the industry.
More details on the three tasks can be found in the respective task page in the menu to the left.
Please do not hesitate to contact the WP leaders Dr. Corinna Möhrlen and Dr. Ricardo Bessa or task leaders (right side), if you would like to get more information or are interested in contributing with your expertise to any of the undertaking efforts.
+45 46 77 50 95
DTU Wind Energy
DTU Risø Campus
Monday to Friday
9 am – 17 pm Central European Time