IEA Wind Recommended Practice for the Implementation of Renewable Energy Forecasting Solutions

1st Edition - November 12, 2022
Authors: Corinna Möhrlen, John W. Zack, Gregor Giebel
Language: English
Paperback ISBN:
9 7 8 - 0 - 4 4 3 - 1 8 6 8 1 - 3
eBook ISBN:
9 7 8 - 0 - 4 4 3 - 1 8 6 8 2 - 0

Published as an Open Access book available on Science Direct, IEA Wind Recommended Practices for the Implementation of Renewable Energy Forecasting Solutions translates decad… Read more

IEA Wind Recommended Practice for the Implementation of Renewable Energy Forecasting Solutions

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Published as an Open Access book available on Science Direct, IEA Wind Recommended Practices for the Implementation of Renewable Energy Forecasting Solutions translates decades of academic knowledge and standard requirements into applicable procedures and decision support tools for the energy industry. Designed specifically for practitioners in the energy industry, readers will find the tools to maximize the value of renewable energy forecast information in operational decision-making applications and significantly reduce the costs of integrating large amounts of wind and solar generation assets into grid systems through more efficient management of the renewable generation variability.

Authored by a group of international experts as part of the IEA Wind Task 36 (Wind Energy Forecasting), the book addresses the issue that many current operational forecast solutions are not properly optimized for their intended applications. It provides detailed guidelines and recommended practices on forecast solution selection processes, designing and executing forecasting benchmarks and trials, forecast solution evaluation, verification, and validation, and meteorological and power data requirements for real-time forecasting applications. In addition, the guidelines integrate probabilistic forecasting, integrate wind and solar forecasting, offer improved IT data exchange and data format standards, and have a dedicated section to dealing with the requirements for SCADA and meteorological measurements.

A unique and comprehensive reference, IEA Wind Recommended Practices for the Implementation of Renewable Energy Forecasting Solutions is an essential guide for all practitioners involved in wind and solar energy generation forecasting from forecast vendors to end-users of renewable forecasting solutions.

Cover image
Title page
Table of Contents
Copyright
Dedication
List of figures
Bibliography
List of tables
Bibliography
Biography
Dr. Corinna Möhrlen
Dr. John W. Zack
Dr. Gregor Giebel
Preface
About the IEA Wind TCP and Task 36 and 51
Part One: Forecast solution selection process
Introduction
Chapter One: Forecast solution selection process
1.1. Before you start reading
1.2. Background and introduction
1.3. Objectives
1.4. Definitions
Chapter Two: Initial considerations
2.1. Tackling the task of engaging a forecaster for the first time
2.2. Purpose and requirements of a forecasting solution
2.3. Adding uncertainty forecasts to forecasting solutions
2.4. Information table for specific topic targets
Bibliography
Chapter Three: Decision support tool
3.1. Initial forecast system planning
3.2. IT infrastructure considerations
3.3. Establishment of a requirement list
3.4. Short-term solution
3.5. Long-term solution
3.6. Going forward with an established IT system
3.7. Complexity level of the existing IT solution
3.8. Selection of a new vendor versus benchmarking existing vendor
3.9. RFP evaluation criteria for a forecast solution
3.10. Forecast methodology selection for use of probabilistic forecasts
Bibliography
Chapter Four: Data communication
4.1. Terminology
4.2. Data description
4.3. Data format and exchange
4.4. Sample formatted template files and schemas
Bibliography
Chapter Five: Concluding remarks
Part Two: Designing and executing forecasting benchmarks and trials
Introduction
Chapter Six: Designing and executing benchmarks and trials
6.1. Before you start reading
6.2. Background and introduction
6.3. Definitions
6.4. Objectives
Chapter Seven: Initial considerations
7.1. Deciding whether to conduct a trial or benchmark
7.2. Benefits of trials and benchmarks
7.3. Limitations with trials and benchmarks
7.4. Time lines and forecast periods in a trial or benchmark
7.5. 1-Page “cheat sheet” checklist
Bibliography
Chapter Eight: Conducting a benchmark or trial
8.1. Phase 1: preparation
8.2. Phase 2: During benchmark/trial
8.3. Phase 3: Post trial or benchmark
Bibliography
Chapter Nine: Considerations for probabilistic benchmarks and trials
9.1. Preparation phase challenges for probabilistic b/t
9.2. Evaluation challenges for probabilistic b/t
Bibliography
Chapter Ten: Best practice recommendations for benchmarks/trials
10.1. Best practice for b/t
10.2. Pitfalls to avoid
Part Three: Forecast solution evaluation
Introduction
Chapter Eleven: Forecast solution evaluation
11.1. Before you start reading
11.2. Background and introduction
Bibliography
Chapter Twelve: Overview of evaluation uncertainty
12.1. Representativeness
12.2. Significance
12.3. Relevance
Bibliography
Chapter Thirteen: Measurement data processing and control
13.1. Uncertainty of instrumentation signals and measurements
13.2. Measurement data reporting and collection
13.3. Measurement data processing and archiving
13.4. Quality assurance and quality control
Chapter Fourteen: Assessment of forecast performance
14.1. Forecast attributes at metric selection
14.2. Prediction intervals and predictive distributions
14.3. Probabilistic forecast assessment methods
14.4. Metric-based forecast optimization
14.5. Post-processing of ensemble forecasts
Bibliography
Chapter Fifteen: Best practice recommendations for forecast evaluation
15.1. Developing an evaluation framework
15.2. Operational forecast value maximization
15.3. Evaluation of benchmarks and trials
15.4. Use cases
Bibliography
Part Four: Meteorological and power data requirements for real-time forecasting applications
Introduction
Chapter Sixteen: Meteorological and power data requirements for real-time forecasting applications
16.1. Before you start reading
16.2. Background and introduction
16.3. Structure and recommended use
Bibliography
Chapter Seventeen: Use and application of real-time meteorological measurements
17.1. Application-specific requirements
17.2. Available and applicable standards for real-time meteorological and power measurements
17.3. Standards and guidelines for general meteorological measurements
17.4. Data communication
Bibliography
Chapter Eighteen: Meteorological instrumentation for real-time operation
18.1. Instrumentation for wind projects
18.2. Instrumentation for solar projects
Bibliography
Chapter Nineteen: Power measurements for real-time operation
19.1. Live power and related measurements
19.2. Measurement systems
19.3. Power available signals
19.4. Live power data in forecasting
19.5. Summary of best practices
Chapter Twenty: Measurement setup and calibration
20.1. Selection of instrumentation
20.2. Location of measurements
20.3. Maintenance and inspection schedules
Bibliography
Chapter Twenty-One: Assessment of instrumentation performance
21.1. Measurement data processing
21.2. Uncertainty expression in measurements
21.3. Known issues of uncertainty in specific instrumentation
21.4. General data quality control and quality assurance (QCQA)
21.5. Historic quality control (QC)
21.6. Real-time quality control (QC)
Bibliography
Chapter Twenty-Two: Best practice recommendations
22.1. Definitions
22.2. Instrumentation
22.3. Recommendations for real-time measurements by application type
22.4. Recommendations for real-time measurements for power grid and utility-scale operation
22.5. Recommendations for real-time measurements for power plant operation and monitoring
22.6. Recommendations for real-time measurements for power trading in electricity markets
Bibliography
Chapter Twenty-Three: End note
Appendix A: Clarification questions for forecast solutions
Ask questions to the vendors
Appendix B: Typical RFI questions prior to or in an RFP
Appendix C: Application examples for use of probabilistic uncertainty forecasts
C.1. Example of the graphical visualization of an operational dynamic reserve prediction system at a system operator
C.2. High-speed shut down warning system
Appendix D: Metadata checklist
Appendix E: Sample forecast file structures
E.1. XSD template example for forecasts and SCADA
E.2. XSD SCADA template for exchange of real-time measurements
Appendix F: Standard statistical metrics
F.1. BIAS
F.2. MAE – mean absolute error
F.3. RMSE – root mean squared error
F.4. Correlation
F.5. Standard deviation
F.6. What makes a forecast “good”?
Bibliography
Appendix G: Validation and verification code examples
G.1. IEA wind task 36 and task 51 specific V&V code examples
G.2. Code examples from related projects with relevance to recommendations
Bibliography
Appendix H: Examples of system operator met measurement requirements
H.1. Examples of requirements in different jurisdictions
H.2. Met measurement requirement example from California independent system operator in USA
H.3. Met measurement requirement example from Irish system operator EIRGRID group
H.4. Met measurement requirement example from Alberta electric system operator in Canada
Bibliography
Bibliography
Bibliography
Nomenclature
Bibliography
Index

Corinna Möhrlen

Dr. Corinna Möhrlen earned a Masters degree in Civil Engineering from Ruhr-University Bochum, Germany and a Masters and PhD degree from University College Cork, Ireland, where she started her career in the wind energy area in 2000, being responsible for the development of wind energy forecasting in Ireland in collaboration with the Danish Meteorological Institute. She is co-founder and managing director of WEPROG. Founded in 2003, WEPROG provides world-wide operational weather ensemble and energy forecasting services and is highly specialised in the energy industry's renewables integration. Over the past 20 years Corinna gained experience in integrating renewables into real-time operations, served as coordinator and participant in R&D projects, actively writes and reviews journal articles, organises and participates in workshops and advices on application of ensemble forecasting to deal with uncertainties related to renewable energy generation. Corinna is a board member and workpackage 3 leader of the IEA Wind Task 36 "Wind Energy Forecasting" and received an ESIG excellence award for contributions to advances in the use of probabilistic forecasting in 2020.

Affiliations and expertise

WEPROGApS, Assens, Denmark

John W. Zack

Dr. John W. Zack earned a BS degree in meteorology and oceanography from New York University and a Ph.D. in atmospheric sciences from Cornell University. He is the President, Chief Scientist and co-founder of MESO, Inc., a 35-year-old small business that specializes in the development and application of physics-based and statistical geophysical models. He is also a Senior Advisor at UL Services Group after leaving his full-time position as the head of the company’s Grid Solutions division in 2018. In 1998, he was one of the founding partners of AWS Truepower, a global leader in renewable energy consulting services, and served on its Board of Directors until its acquisition by UL, Inc in 2016. John is a board member and workpackage 2 leader of the IEA Wind Task 36 "Wind Energy Forecasting" and received an ESIG excellence award for contributions to advances in the use of probabilistic forecasting in 2020.

Affiliations and expertise

MESO, Inc., New York University, USA

Gregor Giebel

Dr. Gregor Giebel has worked for over 25 years with short-term forecasting of wind power, large-scale integration of wind power into electricity grids, wind farm flow control and condition monitoring for wind turbines including standardisation within the IEC. He is Operating Agent of IEA Wind Task 36 Forecasting for Wind Energy, and heads the FarmConners EU Coordination Action on wind farm control (windfarmcontrol.info) and the EU Marie Curie Initial Training Network Train2Wind (train2wind.eu). His main claim to fame is the standard report on the state of the art in short-term forecasting, with over 950 citations. He also is an accomplished writer of research proposals, with a funding quota of over 50%.

Affiliations and expertise

Department of Wind & Energy Systems, Technical University of Denmark, Denmark

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IEA Wind Recommended Practice for the Implementation of Renewable Energy Forecasting Solutions

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Corinna Möhrlen

John W. Zack

Gregor Giebel