Issues with Data Quality for Wind Turbine Condition Monitoring and Reliability Analyses

Kevin Leahy, Colm Gallagher, Peter O’Donovan and Dominic T. J. O’Sullivan
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Kevin Leahy: School of Engineering, University College Cork, Cork T12 K8AF, Ireland
Colm Gallagher: School of Engineering, University College Cork, Cork T12 K8AF, Ireland
Peter O’Donovan: School of Engineering, University College Cork, Cork T12 K8AF, Ireland
Dominic T. J. O’Sullivan: School of Engineering, University College Cork, Cork T12 K8AF, Ireland

Energies, 2019, vol. 12, issue 2, 1-22

Abstract: In order to remain competitive, wind turbines must be reliable machines with efficient and effective maintenance strategies. However, thus far, wind turbine reliability information has been closely guarded by the original equipment manufacturers (OEMs), and turbine reliability studies often rely on data that are not always in a usable or consistent format. In addition, issues with turbine maintenance logs and alarm system data can make it hard to identify historical periods of faulty operation. This means that building new and effective data-driven condition monitoring techniques and methods can be challenging, especially those that rely on supervisory control and data acquisition (SCADA) system data. Such data are rarely standardised, resulting in challenges for researchers in contextualising these data. This work aims to summarise some of the issues seen in previous studies, highlighting the common problems seen by researchers working in the areas of condition monitoring and reliability analysis. Standards and policy initiatives that aim to alleviate some of these problems are given, and a summary of their recommendations is presented. The main finding from this work is that industry would benefit hugely from unified standards for turbine taxonomies, alarm codes, SCADA operational data and maintenance and fault reporting.

Keywords: wind turbines; SCADA data; reliability; condition monitoring; data quality (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

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