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Wind Energy
Article . 2022 . Peer-reviewed
License: CC BY
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Wind Energy
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Wind Energy
Article . 2023
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Field‐data‐based reliability analysis of power converters in wind turbines: Assessing the effect of explanatory variables

Authors: Karoline Pelka; Katharina Fischer;

Field‐data‐based reliability analysis of power converters in wind turbines: Assessing the effect of explanatory variables

Abstract

AbstractFrequent failures of power converters affect the availability of wind turbines and cause considerable maintenance costs. To enhance the reliability of power converters in wind turbines, the prevailing causes and modes of failures have to be identified. This publication contributes to root‐cause analysis of the power‐converter failures in wind turbines from a statistical point of view. For this purpose, the failure behavior of power‐converters is modeled via lifetime models as well as repairable‐system models. By means of regression models, covariates are incorporated, including both design‐related and site‐specific covariates. The analysis is based on a worldwide extensive field‐data collection covering more than 9000 turbines, including different turbine designs, sites, and ages. The results obtained by means of the applied regression models indicate that the location of the power converter within the turbine, the cooling system, the converter rated power, the DC‐link voltage, the IGBT‐module manufacturer, and the commissioning date of the turbine as design‐related covariates have a significant effect on the phase‐module failure behavior and with that on converter reliability. Among the site‐specific covariates, the analysis results confirm humidity as a likely significant driver of failures.

Keywords

reliability, regression models, field reliability data, TJ807-830, Renewable energy sources, wind turbines, power converter

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    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
gold