© Faculty of Mechanical Engineering, Belgrade. All rights reserved FME Transactions (2015) 43, 319-327 319 Received: October 2015, Accepted: November 2015 Correspondence to: Dr. Leonilde Varela University of Minho, Campus of Azurem, 4800-058 Guimaraes, Portugal, mail: leonilde@dps.uminho.pt doi:10.5937/fmet1504319A Hadi Abdollahzadeh Malek Ashtar University of Technology Department of Industrial Engineering 15875-1774, Tehran, Iran Leonilde Varela University o Minho School of Engineering Department of Production and Systems 4804 – 533, Guimarães, Portugal Karim Atashgar Malek Ashtar University of Technology Department of Industrial Engineering 15875-1774, Tehran, Iran Goran D. Putnik University o Minho School of Engineering Department of Production and Systems 4804 – 533, Guimarães, Portugal Condition Based Maintenance Optimization for Multi-State Wind Power Generation Systems under Periodic Inspection As the wind power system moves toward more efficient operation, one of the main challenges for managers is to determine a cost effective maintenance strategy. Most maintenance optimization studies for wind power generation systems deal with wind turbine components separately. However, there are economic dependencies among wind turbines and their components. In addition, most current researches assume that the components in a wind turbine only have two states, while condition monitoring techniques can often provide more detailed health information of components. This study aims to construct an optimal condition based maintenance model for a multi-state wind farm under the condition that individual components or subsystems can be monitored in periodic inspection. The results are demonstrated using a numerical example. Keywords: Multi-state; Wind farm; Economic dependence, Periodic inspection, Condition based maintenance, Three-phase simulation. 1. INTRODUCTION Wind farms (WF) have been used around the world both onshore and offshore as a cleaner way of generating electricity. WFs are multi-component systems and they are often located in remote areas or off-shore sites. There are economic dependencies among wind turbines (WT) and their components. Opportunistic maintenance policies can be an effective maintenance approach in a WF [1, 2]. Most opportunistic maintenance studies of WFs was focused on corrective deployment of maintenance groups. That is, maintenance teams are deployed to the WF only when a failure occurs. Almgren et. al. [3] considered an optimization model for determining optimal opportunistic replacement of component. Patriksson et. al. [4, 5] extended the model in Ref. [3] by considering a stochastic programming approach. Ding and Tian [6] dealt with the study of an opportunistic maintenance policy based on the component’s age threshold values. Ding and Tian [7] further extended the model to accommodate different age thresholds between functional turbines and failed turbines. Tian et. al [8] developed a condition based maintenance method, based on two failure probability threshold values and the condition monitoring data. Many of the reported work on maintenance optimization of WF assume that the system is composed of a number of components which have only two working states. However, WF structure is made up of a number of WTs which are composed of several multi-state components. In addition, the above-mentioned works assumed that components are monitored continuously. However, continuous monitoring of a WT is not always practicable. For such systems, data are usually collected intermittently and analyzed by experienced condition monitoring engineers [9]. Therefore, inspection intervals should be optimized when the inspection cost is not negligible. To address the above issues, in this paper a new opportunistic maintenance optimization approach for a WF considering the economic dependence among WT is introduced. It is assumed that each WT may be inspected at discrete time intervals. The optimization approach is to minimize the expected maintenance cost with respect to availability constraint. To model the behaviour of different entities of the system and to evaluate main performance measures, a three-phase discrete event simulation is introduced. This paper is organized as follows: in section 2 features of the problem are presented. Section 3 defines the proposed performance evaluation method. The mathematical model is described in section 4. An example is also shown in section 5, while concluding remarks are presented in section 6. 2. PROBLEM DESCRIPTION Suppose that there are k types of WTs in a WF, and also, M i WT of type i (i=1,2,..,k) have been installed in a WF. We assume that each turbine type has N critical component connected in series. The components in a WT are assumed to deteriorate over time, and the degradation processes follow a multi-state model. The number of the health state of the jth (j=1,2,…,N) component of each WT can be represented by a finite set of discrete states { } j j m , , 2 , 1 … = ψ . State 1 is the initial health state of the component, and states 2,…,(m j -1) reflect its deteriorating conditions. The degradation process is represented by the transition from one state to another state. Each state d (d=1,2,…,m j ) is characterized