Task 51 Recommended Practices

Recommended Practice

Recommended Practice on Renewable Energy Forecast Solution Selection

The Executive Committee of the International Energy Agency Wind Technology Collaboration Programme (widely referred to as “IEA Wind“) has in January 2022 approved for release the first set of internationally accepted industry guidelines for renewable power forecasting entitled, “IEA Wind Recommended Practice for the Implementation of Renewable Energy Forecasting Solutions” which as published by Elsevier as an OpenAccess electronic and paperback book on November, 11 2022. The ultimate objective of this set of documents is to:

maximize the value of renewable energy forecast information in operational decision-making applications
significantly reduce the costs of integrating large amounts of wind and solar generation assets into grid systems and markets through more efficient management of the renewable generation variability

It addresses the issue that many current operational forecast solutions are not properly optimized for their intended applications, and many will most likely fail to let us as societies move towards high shares of renewables on the grid. The documents were authored by a group of international experts, which collaborated within one of the activities under IEA Wind Task 36 (Wind Power Forecasting) and Task 51 (Forecasting for the weather-driven Energy System). The group of experts included researchers from universities and government laboratories, commercial forecast providers, and users of operational forecasts. The set consists of four documents:

Presentations and Use-Case Publications of the Recommended Practice Guideline

The first workshop was held at the International Conference on Energy and Meteorology in June 2019. The presentation with results from that workshop is published on the Task 36 website. The second of these workshops was held on 17 October 2019 in conjunction with the 18th International Wind Integration Workshop in Dublin, Ireland. There was another Open Space Workshop, and the questions and results are presented in this paper. We also discussed this at the IEA Task 36 Workshop in Glasgow, 21 January 2020. The results of the discussion are in this paper, and if you prefer video, it is here.

In 2022, John Zack and Corinna Möhrlen presented the revised second edition of the recommended practice guidelines at the American Meteorological Society Annual Meeting’s 13th Conference on Weather, Climate, and the New Energy Economy in the Core Science Keynote session 11.1 – Best Practices for the Selection of Optimal Forecast Solutions for Renewable Electricity Generation Applications. The presentation can be downloaded here or in the Publication section in the “Workshops & Special Sessions“.

In 2023, Corinna Möhrlen presented at the 22nd Wind & Solar Integration Workshop in Copenhagen, some use-cases for the application of the verification tool that is being developed within the IEA Wind Task 51 according to the Recommended Practice as a R-package (“WE-verify-prob”), programmed by Mathias Blicher Bjerregaard and Jethro Browell ( Link to presentation and paper – see also Workshop & Articles Publication menu for download )

Collaboration with IEC Sub-Committee 8A Grid Integration of Renewable Energy

In June 2023, the IEA Wind Task 51 teamed up with the IEC Sub-Committee 8A Grid Integration of Renewable Energy Generation and decided at a workshop held in Copenhagen to pursue the development of a standard for forecasting of renewable energy. In October 2023, the New Wok Item was accepted by all members in the IEC SC8A work group 2.

In 2024, Corinna Möhrlen and John Zack chaired a session at the Wind & Solar integration Workshop in Helsinki, Finland. Session 9D – IEC SC8A – IEA FORECASTING STANDARD was dedicated to present the collaboration to develop a standard for forecasting of Renewables by IEA Wind Task 51 and IEC Sub-committee 8A Workgroup 2. There were 3 presentations and a panel discussion to present the current status of the work and to get feedback from the audience. An Introduction to the IEC and IEA liaison for the Collaborative Development of a Standard for Renewables Forecasting and Forecast Evaluation was provided by Corinna Möhrlen. Frank Martin, the chair of IEC SC8A provided an Overview of the IEC Sub-Comittee 8A on Grid Integration of Renewable Energy Generation and Zheng Wang, the assistant of the WG chair added an Overview of the IEC Sub-Comittee 8A Workgroup 2 on Renewable energy power prediction.

Download

IEA Wind Recommended Practice for the Implementation of Renewable Energy Forecasting Solutions. 270 pp. Elsevier Academic Press, November 1, 2022. ISBN: 9780443186813.

Elsevier OpenAccess electronic book for download here

Elsevier printed book: order here

Edition 2

(accepted by IEA Wind Executive Committee, Feb. 2022):
Major updates in comparison to Edition 1:

Probabilistic Forecast Solution selection and evaluation in parts 1,2 and 3
Data communication and formats in part 1 with referral in parts 2 and 3
Application and Evaluation examples

Edition 1

(Accepted by IEA Wind Executive Committee and Published Sept. 2019):

Part 1: Forecast Solution Selection Process
Part 2: Designing and Executing Forecasting Benchmarks and Trials
Part 3: Evaluation of Forecasts and Forecast Solutions

Alternatively, download all as one document or download a shorter version in this handout.

Please send your feedback, question, or suggestion to Corinna Möhrlen here

Verification Code Examples :

IEA WIND TASK 36 AND TASK 51 SPECIFIC V&V CODE EXAMPLES

The following code examples have been specifically developed under IEA Wind Task 36 “Forecasting for Wind Energy” or Task 51 “Forecasting for a Weather Driven Energy system” projects and build a good basis for the development of a evaluation framework as recommended in chapter 15, section 15.1 of the Recommended Practice for the implementation of renewable energy forecast solutions

WE-Validate:

Python-based code base as a platform to consistently evaluate wind-
power forecasts. The tool WE-Validate is meant to gear towards forecast validation
using observations and simulations for wind energy (WE) applications. This infras-
tructure code enables comparison of time series from arbitrary data sources using user-
defined metrics. The tool is designed to be simple, readily usable, open source, pub-
licly available, modularized, and extensible by users. We have detailed instructions for
users on its GitHub page, Accessible Online: https://github.com/joejoeyjoseph/

WE-verify-prob:

R-based example code base to verify probabilistic wind energy
forecasts. The tool WE-verify-prob is a project initiated within the IEA Wind Task
36 and 51 in order to provide example code to the IEA Wind Recommended Practice
for the Implemention of Renewable Energy Forecast Solutions Part 2 Designing and
Executing Forecasting Benchmarks and Trials and 3 Forecast Solution Evaluation.

Accessible for download here:

Short Summary of the Recommended Practice for the Implementation of Renewable Energy Forecasting Solutions

The first of the three documents is entitled “Forecast Solution Selection Process“. It provides guidance via a decision support tool for the design and implementation of a process to select an optimal forecast solution for a specific application. The second document in the set deals with “Designing and Executing Forecasting Benchmarks and Trials“. This part provides recommendations on how to design and execute a forecasting trial to provide high-quality information that can be used to cost-effectively identify the best forecast solution for a user’s set of applications. The third document “Evaluation of Forecasts and Forecast Solutions” provides guidance on how to formulate an evaluation process to obtain representative, significant and relevant information about an existing forecast solution or differences in forecast performance among a set of candidate solutions. The guideline also encourages forecast users to establish a framework of metrics that help identify, whether the user’s forecast performance criteria effectively incentivize the forecast provider to optimize towards the forecast target variable that has the most value for the user’s application(s). The fourth part “Meteorological and Power Data Requirements for real-time forecasting Applications“, provides guidance for the selection, deployment, and maintenance of meteorological sensors and the quality control of the data produced by those sensors with the objective of maximizing the value of the sensor data for real-time wind and solar power production forecasting.