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This paper deals with the problem of estimation maintenance costs for the case of the pitch controls system of wind farms turbines. Previous investigations have estimated these costs as (traditional) "crisp" values, simply ignoring the uncertainty nature of data and information available. This paper purposes an extended version of the estimation model by making use of the Fuzzy Set Theory. The results alert decision-makers to consequent uncertainty of the estimations along with their overall level, thus improving the information given to the maintenance support system.

Wind turbines are nowadays the principal source of wind energy production. However, the technical information publicly known about these machines is still very scarce. Indeed, information related to failure modes, unavailability and maintenance costs of these systems remains confidential and only is held by manufacturers. To be able to optimize the efficiency, to guarantee the security and to negotiate better warranty and maintenance contracts, it is necessary to know more information about the operation and maintenance and replacement costs of subsystems of a wind turbine. To this end, this paper presents a short literature review of what has been published so far about this issue, and, based on two years of operation, analyses an active power control system of 21 identical wind turbines, installed in a wind farm in Portugal. The emphasis of this study is on the operation, availability and maintenance, and replacement costs of the active pitch control device, which automatically manages the position and operation of blades according to wind direction and speed, thus maximizing the electrical power gathered from the natural forces. Moreover, the paper provides an estimation for the total maintenance cost of this device, one of the most important components of the wind turbine, thus allowing wind farm companies to carry out financial and economic analysis of maintenance contracts that probably will be the rationale for better contract negotiations with manufactures. The result and the analyses that have been reported may also contribute for further studies on the reliability and maintenance policies of wind turbines.