Recommended practices for wind farm data collection and reliability assessment for O&amp;M optimization

Hahn, B.; Welte, Thomas Michael; Faulstich, Stefan; Bangalore, Pramod; Boussion, Cyril; Harrison, Kevin; Miguelanez-Martin, Emilio; O'Connor, Frank; Pettersson, Lasse H.; Soraghan, Conaill; Stock-Williams, C.F.W.; Sørensen, John Dalsgaard; Bussel, Gerard van; Vatn, Jørn

doi:10.1016/j.egypro.2017.10.360

Cited by 16 publications

(15 citation statements)

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“…Recommendations on how to collect data for the purpose of reliability assessment are summarized in [5]. However real-world data is often not collected according to this recommendation.…”

Section: State Of Research On Approaches For Digitalization Of Mainte...mentioning

confidence: 99%

Digitalization Workflow for Automated Structuring and Standardization of Maintenance Information of Wind Turbines into Domain Standard as a Basis for Reliability KPI Calculation

Lutz

Walgern

Beckh

et al. 2022

J. Phys.: Conf. Ser.

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Maintenance data of wind turbines is an important information source for calculating key performance indicators. Also, it can be used for developing models for early fault detection. Both activities aim for supporting informed decisions in operation and maintenance. However, such data is rarely available in a structured and standardized format which hinders the interoperability of different enterprises. Consequently, maintenance information is often unused or only usable with considerable personnel effort. To digitalize wind farm maintenance, a digitalization workflow is developed and presented in this paper. The workflow consists of the steps optical character recognition, information extraction and text classification. The workflow is applied on real-world wind turbine service reports and invoices. First results for each step show good performance metrics and potential for further real-world application of the proposed method.

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“…Recommendations on how to collect data for the purpose of reliability assessment are summarized in [5]. However real-world data is often not collected according to this recommendation.…”

Section: State Of Research On Approaches For Digitalization Of Mainte...mentioning

confidence: 99%

Digitalization Workflow for Automated Structuring and Standardization of Maintenance Information of Wind Turbines into Domain Standard as a Basis for Reliability KPI Calculation

Lutz

Walgern

Beckh

et al. 2022

J. Phys.: Conf. Ser.

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“…Estos datos de funcionamiento y valores de medición, además de ser utilizados para la detección de fallas, deben ser almacenados y estar disponibles para análisis posteriores, como el presentado en este documento. Sin embargo, para poder realizar análisis más sólidos se requieren varios grupos de datos, como los mencionados anteriormente: datos del equipo, datos de mantenimiento e inspección, datos de fallas e información de costos [15].…”

Section: Detección De Fallasunclassified

Metodología FMECA para un aerogenerador doblemente alimentado

et al. 2021

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Debido a la complejidad de los sistemas eólicos, la necesidad de contar con aerogeneradores fiables es de suma importancia, por ello se han desarrollado metodologías para mejorar sus características y desempeño. El método de análisis de modos de falla, efectos y criticidad se ha utilizado para estudiar la confiabilidad de diferentes sistemas de generación de energía. En este documento se presenta la aplicación de dicha metodología a un aerogenerador de inducción doblemente alimentado, para realizar una evaluación cualitativa y cuantitativa de las características de falla en el mismo. Además, para tomar en cuenta consideraciones económicas en el análisis, se presenta el enfoque del método basado en el riesgo, con el fin de mitigar las limitaciones que presenta el método tradicional. Como resultado se determina que la prioridad de atención debe enfocarse en el generador, luego el sistema eléctrico y posteriormente en las palas.

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“…As the idea to provide uncertainties for theses KPIs is misleading, they are excluded as well. According to Hahn et al [20], standardization of the collected data and a review of documentation processes provides much more utility in this case. To select a total of five KPIs for further assessment out of the remaining KPIs, the prioritization of KPIs, as provided by [6], is used.…”

Section: Key Performance Indicatorsmentioning

confidence: 99%

Considering Uncertainties of Key Performance Indicators in Wind Turbine Operation

2020

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Key performance indicators (KPIs) are commonly used in the wind industry to support decision-making and to prioritize the work throughout a wind turbine portfolio. Still, there is little knowledge of the uncertainties of KPIs. This article intends to shed some light on the uncertainty and reliability of KPIs in general and performance KPIs in particular. For this purpose, different uncertainty causes are discussed, and three data handling related uncertainty causes are analyzed in detail for five KPIs. A local sensitivity analysis is followed by a more detailed analysis of the related uncertainties. The work bases on different sets of operational data, which are manipulated in a large number of experiments to carry out an empirical uncertainty analysis. The results show that changes in the data resolution, data availability, as well as missing inputs, can cause considerable uncertainties. These uncertainties can be reduced or even mitigated by simple measures in many cases. This article provides a comprehensive list of statements and recommendations to estimate the relevance of data handling related KPI uncertainties in the day-to-day work as well as approaches to correct KPIs for systematic deviations and simple steps to avoid pitfalls.

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Recommended practices for wind farm data collection and reliability assessment for O&M optimization

Cited by 16 publications

References 1 publication

Digitalization Workflow for Automated Structuring and Standardization of Maintenance Information of Wind Turbines into Domain Standard as a Basis for Reliability KPI Calculation

Digitalization Workflow for Automated Structuring and Standardization of Maintenance Information of Wind Turbines into Domain Standard as a Basis for Reliability KPI Calculation

Metodología FMECA para un aerogenerador doblemente alimentado

Considering Uncertainties of Key Performance Indicators in Wind Turbine Operation

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