• Aucun résultat trouvé

IEA Wind Task 36 Forecasting-Phase II

N/A
N/A
Protected

Academic year: 2021

Partager "IEA Wind Task 36 Forecasting-Phase II"

Copied!
2
0
0

Texte intégral

(1)

HAL Id: hal-02159510

https://hal.archives-ouvertes.fr/hal-02159510

Submitted on 18 Jun 2019

HAL is a multi-disciplinary open access

archive for the deposit and dissemination of

sci-entific research documents, whether they are

pub-lished or not. The documents may come from

teaching and research institutions in France or

abroad, or from public or private research centers.

L’archive ouverte pluridisciplinaire HAL, est

destinée au dépôt et à la diffusion de documents

scientifiques de niveau recherche, publiés ou non,

émanant des établissements d’enseignement et de

recherche français ou étrangers, des laboratoires

publics ou privés.

Distributed under a Creative Commons Attribution| 4.0 International License

IEA Wind Task 36 Forecasting-Phase II

Gregor Giebel, Will Shaw, Helmut Frank, Pierre Pinson, Georges

Kariniotakis, Caroline Draxl, Corinna Möhrlen

To cite this version:

Gregor Giebel, Will Shaw, Helmut Frank, Pierre Pinson, Georges Kariniotakis, et al.. IEA Wind Task

36 Forecasting-Phase II. Geophysical Research Abstracts, Apr 2019, Vienna, Austria. 21, pp.EGU2019

- 16557. �hal-02159510�

(2)

Geophysical Research Abstracts Vol. 21, EGU2019-16557, 2019 EGU General Assembly 2019

© Author(s) 2019. CC Attribution 4.0 license.

IEA Wind Task 36 Forecasting - Phase II

Gregor Giebel (1), Will Shaw (2), Helmut Frank (3), Pierre Pinson (1), Caroline Draxl (4), George Kariniotakis (5), and Corinna Möhrlen (6)

(1) DTU, Risø, Denmark (grgi@dtu.dk), (2) PNNL, Richmond, US, (3) Deutscher Wetterdienst, Offenbach, Germany, (4) NREL, Golden, US, (5) MINES ParisTech, Sophia Antipolis, France, (6) WEPROG

Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The International Energy Agency (IEA) Task on Wind Power Forecasting organises international collaboration, among national weather centres, forecast vendors and forecast users. The Task looks back on the first 3 years, and just started the second three-year period.

Collaboration is open to IEA Wind member states, 13 countries are already therein.

The Task is divided in three work packages: 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 and a benchmark. Secondly, we try to improve the derived power forecasts and deal with forecast vendor related matters to bring the entire industry forward. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions. The main result of the first phase is the IEA Recommended Practice for Selecting Renewable Power Fore-casting Solutions. This document in three parts (Forecast solution selection process, Designing and executing forecasting benchmarks and trials and Benchmark metrics) takes its outset from the recurrent problem at forecast user companies of how to choose a forecast vendor. The first report describes how to tackle the general situation, while the second report specifically describes how to set up a forecasting trial so that the result is what the client intended. Many of the pitfalls we have seen over the years, are avoided.

Other results include a comprehensive review paper on the use of uncertainty forecasts in the power indus-try and an information portal related to forecasting.

In short, the poster presents the IEA Task 36 on Wind Power Forecasting, opening a forum for international collaboration in this important field for meteorologists, wind power forecasters and end users. For collaboration, please contact the author (grgi@dtu.dk) and see the website at www.ieawindforecasting.dk.

Références

Documents relatifs

Two decisions had to be made: (1) a trading decision with information from deterministic forecasts of power production and wind speed and (2) a decision whether or not to change

In the framework of the Anemos project we developed a professional, flexible platform for operating wind power prediction models, laying the main focus on state-of-the-art

This initiative consists in setting up a Virtual Laboratory (ViLab) for the evaluation of state-of-the-art prediction methods and systems, in addition to stimulating

Figure 3: Comparison of NMAE results in the case of the wind farm WF2 situated on a flat terrain.. Figure 4: Comparison of NMAE results in the case of the wind farm WF3 situated on

Generally, for a day-ahead forecast, the output (typically wind speed and direction, in some cases also temperature, atmospheric stability or other measures) of Numerical

Keywords: Wind power, short-term forecasting, confidence intervals, weather stability, on-line software, numerical weather predictions, ensemble forecasting, uncertainty..

The aim of the project is to develop accurate models that substantially outperform current state -of-the -art methods, for onshore and offshore wind power forecasting, exploiting both

Weather forecasts are used with power system component thermal models and a state estimation technique for calculating rating forecasts at different time horizons.. 1