Fault Detection and Isolation for Wind Turbine Electric Pitch System

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

This paper presents a model-based fault detection and isolation scheme applied on electric pitch system of wind turbines. Pitch system is one of the most critical components due to its effect on the operational safety and the dynamics of wind turbines. Faults in this system should be precisely detected to prevent failures and decrease downtime. To detect faults of electric pitch actuators and sensors, an extended kalman filter (EKF) based multiple model adaptive estimation (MMAE) designed to estimate the states of the system. The proposed method is demonstrated in case studies. The simulation results show that the proposed method detects different fault scenarios of wind turbines under the stochastic external condition.
Close

Details

This paper presents a model-based fault detection and isolation scheme applied on electric pitch system of wind turbines. Pitch system is one of the most critical components due to its effect on the operational safety and the dynamics of wind turbines. Faults in this system should be precisely detected to prevent failures and decrease downtime. To detect faults of electric pitch actuators and sensors, an extended kalman filter (EKF) based multiple model adaptive estimation (MMAE) designed to estimate the states of the system. The proposed method is demonstrated in case studies. The simulation results show that the proposed method detects different fault scenarios of wind turbines under the stochastic external condition.
Original languageEnglish
Title of host publicationProceedings of 2017 IEEE 12th International Conference on Power Electronics and Drive Systems (PEDS)
Number of pages6
PublisherIEEE Press
Publication dateDec 2017
Pages618-623
ISBN (Electronic)978-1-5090-2364-6
DOI
StatePublished - Dec 2017
Publication categoryResearch
Peer-reviewedYes
Event2017 IEEE 12th International Conference on Power Electronics and Drive Systems (PEDS) - Honolulu, United States
Duration: 12 Dec 201715 Dec 2017

Conference

Conference2017 IEEE 12th International Conference on Power Electronics and Drive Systems (PEDS)
LandUnited States
ByHonolulu
Periode12/12/201715/12/2017
SeriesIEEE International Conference on Power Electronics and Drive Systems
ISSN2164-5264

Map

ID: 262642715