Long-Term Operational Data Analysis of an In-Service Wind Turbine DFIG

Abstract

While wind turbine (WT) power capacities continue to increase and new offshore developments are being deployed, operation and maintenance (OM) costs continue to rise, becoming the center of attention in the wind energy sector. The electric generator is among the top three contributors to failure rates and downtime of WTs, where the doubly fed induction generator (DFIG) is the dominant technology among variable speed WTs. Thus, the early detection of generator faults, which can be achieved through predictive maintenance, is vital in order to reduce OM costs. The goal of this paper is to analyze a long-term monitoring campaign of an in-service WT equipped with a DFIG. A novel method named the harmonic order tracking analysis is used with two main objectives: first, to facilitate the data interpretation for non-trained maintenance personnel, and second, to reduce the amount of data that must be stored and transferred for the diagnosis of the DFIG. This method is applied and validated for the first time on an operating WT.