PREVCONFI: confiabilidade aplicada na manutenção preventiva de usinas eólicas, com foco em minimização do custo

Abstract

This job makes the assessment of the Reliability and Maintenance of the wind turbine components with the biggest number of failure rate including all the wind turbine sectors using the wind farm historical operational data. After identifying those components, a more adequate maintenance is planned for those components in order to avoid unexpected failures and consequent financial loss by the lack of energy generation. The proposed routine has the focus on minimizing the maintenance costs followed by a consequent availability increase, also improving the energy generation. The job has the reliability study as a basis to be applied to the maintenance. The Weibull Distribution was applied as the probability distribution for this case study. The schedule of maintenance is prepared by a program created in Microsoft Excel called PREVICONF. The program works based on past experiences from a specific wind farm, feeding the program with new data in order to re schedule the maintenances in the most appropriate timing for the analyzed data. Components able to become the wind turbine unavailable for generating energy are considered as critical components and therefore they have their maintenance schedule based on the minimal cost observing the respective failure probability. The PREVICONF contribution is to prepare schedules of maintenance according the need, differently from the standard routines applied to the Wind Farms. The scheduled maintenances currently in place are used to be performed time to time and they are not taking into account the criticality of some components. Most of the maintenance suppliers are only committed to deliver a minimum availability rate, but without contractual responsibility against energy generation. Part of this job is to show to the wind farm owners and maintenance suppliers how much is important a Reliability assessment in order to obtain a bigger financial return by minimizing the maintenance costs and improving energy generation based on an adequate maintenance schedule for each specific wind farm.