Publication detailsDao, Cuong D., Kazemtabrizi, Behzad & Crabtree, Christopher J. (2019). Wind Turbine Reliability Data Review and Impacts on Levelised Cost of Energy. Wind Energy 22(12): 1848-1871.
- Publication type: Journal Article
- ISSN/ISBN: 1095-4244, 1099-1824
- DOI: 10.1002/we.2404
- Keywords: Reliability, wind turbine, failure rate, downtime, uncertainty, levelised cost of energy.
- Further publication details on publisher web site
- Durham Research Online (DRO) - may include full text
Author(s) from Durham
: Reliability is critical to the design, operation, maintenance, and performance assessment and improvement of wind turbines (WTs). This paper systematically reviews publicly available reliability data for both onshore and offshore WTs and investigates the impacts of reliability on the cost of energy. WT failure rates and downtimes, broken down by subassembly, are collated from 18 publicly available databases including over 18000 WTs, corresponding to over 90000 turbine-years. The data are classified based on the types of data collected (failure rate and stop rate) and by onshore and offshore populations. A comprehensive analysis is performed to investigate WT subassembly reliability data variations, identify critical subassemblies, compare onshore and offshore WT reliability, and understand possible sources of uncertainty. Large variations in both failure rates and downtimes are observed, and the skew in failure rate distribution implies that large databases with low failure rates, despite their diverse populations, are less uncertain than more targeted surveys, which are easily skewed by WT type failures. A model is presented to evaluate the levelised cost of energy as a function of WT failure rates and downtimes. A numerical study proves a strong and non-linear relationship between WT reliability and operation and maintenance expenditure as well as annual energy production. Together with the cost analysis model, the findings can help WT operators identify the optimal degree of reliability improvement to minimise the levelised cost of energy.