# New Tendencies in Wind Energy Operation and Maintenance
## 3 Overview of Wind Farm O&M Research
### Maintenance Strategies (M_stra)  
The enormous proliferation of wind farms worldwide has emerged as an alternative to traditional power generation and as a result of economic issues that require control systems in order [32] to optimize the availability and benefits. Some research focuses on finding the best maintenance strategy that minimizes the total cost and maximizes annual energy produced by wind turbines [80]. Based on information inputs of wind farms, developed decision making [10] can be used to identify the best strategies for maintenance and operation. For wind farms, it is essential to implement automatic control and intelligent routines to integrate them into power grid management. For instance, ref. [47] designed an integrated monitoring and maintenance control platform. It is important to have a description of the common failure modes, monitoring techniques, diagnosis methods and an overview of the maintenance [62]. Once the parameters are neglected [58], most of the available literature is about system performance condition monitoring itself. As an example, in [49], online condition monitoring based on the voltages and currents of a wind turbine system is investigated, and in [81], there is a focus on strategies to follow in the maintenance cables of wind farms. Improvements to maintenance strategies are being made, such as the proposal of a model that extends the classical programming maintenance [39] to include the expected market prices and weather conditions. Another paper [82] focuses on improving reliability-centered maintenance, since it presents challenges that are considered to achieve the optimal maintenance of turbines, reaching conclusions such as the need for improvementsto staff training, the use of quantitative methods for decision support in maintenance and an economic model of the organization of maintenance support. As for predictive maintenance strategies, they can focus on the use of this type of maintenance to optimize the operation of wind farms, illustrating [76] how this can be achieved through real-time noise monitoring. Another optimization method for this type of maintenance is the use of singular spectral analysis, with [72] showing that this new technique is useful as a failure indicator in the predictive maintenance of wind farms. Another effective predictive maintenance strategy is based on an approach to risk analysis and code coating [74] for the protection of marine turbine blades, which significantly reduces maintenance costs for this type of park. The blades suffer various faults and replacement will normally result in a long downtime. This downtime and these costs can be reduced, and the maintenance strategy that achieves these goals is called proactive maintenance. [PERSON] et al. [83] presented an approach to optimize the proactive maintenance of offshore wind turbine blades. On the other hand, [PERSON] et al. [84] presented a probabilistic approach to introduce risk measurement indicators, and improved the ECUME tool to provide these indicators. In this sense, an event model (based on Monte Carlo simulation) and the hidden Markov model are introduced to model the evolution of meteorological and marine parameters and assess the risk of inaccessibility. In other works, discrete event systems [61; 85] are used to develop a simulation model that mimics the maintenance operation of the wind farm market size. Each turbine is treated as a separate module for a cost-effective maintenance strategy and the design of a better quality [11] prognostic and health management system was applied. Another improvement is based on the mathematical model of the Markov process and reliability theory [24] between reliability models for wind power generation is developed. Data mining is an innovative technique used to identify faults in various elements of wind turbines, as in [86], where it predicts failures within 1.5 h beforehand. Another promising technique is neural networks to [52] try to detect failures in some equipment and improve maintenance strategies.