Title: Condition-based maintenance of wind power generation systems considering different turbine types and lead times

Authors: Fangfang Ding; Zhigang Tian; Abeer Amayri

Addresses: Department of Mechanical Engineering, University of Alberta, Edmonton, Alberta, T6G 2G8, Canada ' Department of Mechanical Engineering, University of Alberta, Edmonton, Alberta, T6G 2G8, Canada ' Department of Mechanical and Industrial Engineering, Concordia University, 1515 Ste-Catherine Street West, Montreal, H3G 2W1, Canada

Abstract: Condition monitoring measurements, such as vibration data, acoustic emission data, oil analysis data, power voltage and current data, etc., can be obtained from wind turbine components and be utilised to evaluate and predict the health conditions of the components and the turbines. The objective of condition-based maintenance (CBM) is to optimise the predictive maintenance activities based on the condition monitoring and prediction information to minimise the overall costs of wind power generation systems. In existing work, all the wind turbines are assumed to be of the same type and the lead times of different components are assumed to be constant. This is not the case in many practical applications. In this paper, we develop a CBM approach for wind turbine systems considering different types of wind turbines in a wind farm and different lead times for different turbine components, which lead to more accurate modelling of CBM activities in actual wind farms. In the proposed CBM approach, we present a new CBM policy involving two design variables for each turbine type, a method for turbine failure probability evaluation considering different lead times and a CBM cost evaluation method. Numerical examples are provided to demonstrate the proposed CBM approach.

Keywords: condition-based maintenance; CBM; wind turbines; predictive maintenance; turbine types; lead times; optimisation; wind power; energy systems; turbine failure probability evaluation.

DOI: 10.1504/IJSEAM.2014.063883

International Journal of Strategic Engineering Asset Management, 2014 Vol.2 No.1, pp.63 - 79

Published online: 30 Aug 2014 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article