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

Abstract

Abstract Frequent 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

• field reliability data
• power converter
• regression models
• reliability
• wind turbines