Recommended key performance indicators for operational management of wind turbines
Abstract
Operational managers of wind turbines usually monitor a big fleet of turbines and thus need highly condensed information to identify underperforming turbines and to prioritize their work. Key performance indicators (KPIs) are a solid and frequently used tool for this purpose. However, the KPIs used in the wind industry are not unified to date, which makes comparison in the industry difficult. Further, comprehensive standards on a set of KPIs for the wind industry are missing. This article identifies and recommends KPIs and provides detailed definitions to make KPIs comparable and to enable benchmarking. The starting point of this work is an industry survey with 28 participants intended to identify commonly used KPIs, collect various possible definitions, and prioritize them. Out of a total of 50 KPIs, we discuss in a next step 33 selected KPIs on performance, maintenance, and reliability in detail and recommend definitions, most of which are based on international standards. As a result, operators can easily use these recommendations to base their system of KPIs. By using this unified set of KPIs, operators can be well-prepared to conduct industrywide comparisons and benchmarks. The survey and this article will also serve as a basis for committee work ofmore »
- Authors:
-
[2]
- Fraunhofer Inst. for Energy Economics and Energy System Technology, Kassel (Germany)
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Publication Date:
- Research Org.:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
- OSTI Identifier:
- 1602689
- Report Number(s):
- NREL-JA-5000-72373
Journal ID: ISSN 1742-6588
- Grant/Contract Number:
- AC36-08GO28308
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Physics. Conference Series
- Additional Journal Information:
- Journal Volume: 1356; Journal ID: ISSN 1742-6588
- Publisher:
- IOP Publishing
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 17 WIND ENERGY; wind turbines; key performance indicators; performance; reliability; maintenance
Citation Formats
Pfaffel, Sebastian, Faulstich, Stefan, and Sheng, Shawn S. Recommended key performance indicators for operational management of wind turbines. United States: N. p., 2019.
Web. doi:10.1088/1742-6596/1356/1/012040.
Pfaffel, Sebastian, Faulstich, Stefan, & Sheng, Shawn S. Recommended key performance indicators for operational management of wind turbines. United States. https://doi.org/10.1088/1742-6596/1356/1/012040
Pfaffel, Sebastian, Faulstich, Stefan, and Sheng, Shawn S. Tue .
"Recommended key performance indicators for operational management of wind turbines". United States. https://doi.org/10.1088/1742-6596/1356/1/012040. https://www.osti.gov/servlets/purl/1602689.
@article{osti_1602689,
title = {Recommended key performance indicators for operational management of wind turbines},
author = {Pfaffel, Sebastian and Faulstich, Stefan and Sheng, Shawn S},
abstractNote = {Operational managers of wind turbines usually monitor a big fleet of turbines and thus need highly condensed information to identify underperforming turbines and to prioritize their work. Key performance indicators (KPIs) are a solid and frequently used tool for this purpose. However, the KPIs used in the wind industry are not unified to date, which makes comparison in the industry difficult. Further, comprehensive standards on a set of KPIs for the wind industry are missing. This article identifies and recommends KPIs and provides detailed definitions to make KPIs comparable and to enable benchmarking. The starting point of this work is an industry survey with 28 participants intended to identify commonly used KPIs, collect various possible definitions, and prioritize them. Out of a total of 50 KPIs, we discuss in a next step 33 selected KPIs on performance, maintenance, and reliability in detail and recommend definitions, most of which are based on international standards. As a result, operators can easily use these recommendations to base their system of KPIs. By using this unified set of KPIs, operators can be well-prepared to conduct industrywide comparisons and benchmarks. The survey and this article will also serve as a basis for committee work of the FGW e.V. to develop a corresponding technical guideline.},
doi = {10.1088/1742-6596/1356/1/012040},
journal = {Journal of Physics. Conference Series},
number = ,
volume = 1356,
place = {United States},
year = {Tue Oct 01 00:00:00 EDT 2019},
month = {Tue Oct 01 00:00:00 EDT 2019}
}
Free Publicly Available Full Text
Publisher's Version of Record
Other availability
Search WorldCat to find libraries that may hold this journal
Cited by: 9 works
Citation information provided by
Web of Science
Web of Science
Save to My Library
You must Sign In or Create an Account in order to save documents to your library.
Works referenced in this record:
Effects of turbine technology and land use on wind power resource potential
journal, May 2018
- Rinne, Erkka; Holttinen, Hannele; Kiviluoma, Juha
- Nature Energy, Vol. 3, Issue 6
System LCOE: What are the costs of variable renewables?
journal, December 2013
- Ueckerdt, Falko; Hirth, Lion; Luderer, Gunnar
- Energy, Vol. 63
Wind turbine downtime and its importance for offshore deployment
journal, April 2011
- Faulstich, S.; Hahn, B.; Tavner, P. J.
- Wind Energy, Vol. 14, Issue 3
Capacity factor of wind power realized values vs. estimates
journal, July 2009
- Boccard, Nicolas
- Energy Policy, Vol. 37, Issue 7
Efficiency and effectiveness of wind farms—keys to cost optimized operation and maintenance
journal, November 2003
- Krokoszinski, H. -J.
- Renewable Energy, Vol. 28, Issue 14
Designing an index for assessing wind energy potential
journal, November 2015
- Ritter, Matthias; Shen, Zhiwei; López Cabrera, Brenda
- Renewable Energy, Vol. 83
Measuring operational performance of OSH management system – A demonstration of AHP-based selection of leading key performance indicators
journal, March 2015
- Podgórski, Daniel
- Safety Science, Vol. 73
Key Performance Indicators for Wind Farm Operation and Maintenance
journal, October 2017
- Gonzalez, Elena; Nanos, Emmanouil M.; Seyr, Helene
- Energy Procedia, Vol. 137
A Critical Review on Wind Turbine Power Curve Modelling Techniques and Their Applications in Wind Based Energy Systems
journal, January 2016
- Sohoni, Vaishali; Gupta, S. C.; Nema, R. K.
- Journal of Energy, Vol. 2016
Prioritization of key performance indicators: An integration of analytical hierarchy process and goal setting
journal, March 2007
- Shahin, Arash; Mahbod, M. Ali
- International Journal of Productivity and Performance Management, Vol. 56, Issue 3
A survey on communication networks for electric system automation
journal, May 2006
- Gungor, V. C.; Lambert, F. C.
- Computer Networks, Vol. 50, Issue 7
Application of Data Mining techniques to identify relevant Key Performance Indicators
journal, November 2017
- Peral, Jesús; Maté, Alejandro; Marco, Manuel
- Computer Standards & Interfaces, Vol. 54
Lifetime extension of onshore wind turbines: A review covering Germany, Spain, Denmark, and the UK
journal, February 2018
- Ziegler, Lisa; Gonzalez, Elena; Rubert, Tim
- Renewable and Sustainable Energy Reviews, Vol. 82
Works referencing / citing this record:
Monetary‐based availability: A novel approach to assess the performance of wind turbines
journal, November 2019
- Lutz, Marc‐Alexander; Görg, Philip; Faulstich, Stefan
- Wind Energy, Vol. 23, Issue 1
Considering Uncertainties of Key Performance Indicators in Wind Turbine Operation
journal, January 2020
- Pfaffel, Sebastian; Faulstich, Stefan; Rohrig, Kurt
- Applied Sciences, Vol. 10, Issue 3