# New Tendencies in Wind Energy Operation and Maintenance
## 3 Overview of Wind Farm O&M Research
### Maintenance Optimization (M_OPT)  
There are many types of analysis of maintenance optimization, but many of the research works found are based on optimizing the maintenance of the equipment found inside a wind turbine with different techniques, for example, the analysis of the inspection interval and cost maintenance in gearboxes [73] to obtain optimal maintenance policies, and another optimization method for gearbox maintenance is the given profit maximization [42] of each component per unit time. Studies are also carried out on power generation efficiency analysis [44] connected to a single large power converter operated with variable frequencies, considering wake effects. It is also important for maintenance optimization to have a good detection [118] of nacelle anemometer faults in a wind farm, minimizing the uncertainty. Another optimization is to braking system through the optimization of condition monitoring, as proposed by [PERSON] et al. [49]. Maintenance optimization programs [99] are carried out using Matlab simulation based on a deterministic optimization model [119] to define a maintenance strategy. The research work results could provide opportunities for maintenance strategy optimization, as proposed in [120], by using an artificial neural network. [PERSON] et al. [24] proposed an optimization strategy based on the mathematical model of the Markov process and the reliability theory of a reliability model set of wind power generation. The research work [121] aims to introduce the idea of a complete tool, using software with condition monitoring data of wind turbines to anticipate component failure and it proposes maintenance time and implementation strategies. The research work [10] uses failure prognosis for the optimization of a decision-making methodology to identify the best strategies and have a robust operation and maintenance of a wind turbine. A state-based degradation model for opportunity-based maintenance in offshore wind farms, using a gamma model [122] for the representation of the continuous degradation of components, features the chances of failure to be used in optimization. Control optimization for the distribution of the fatigue of wind turbines in an offshore wind farm on the basis of an intelligent [123] agent theory is a viable way to optimize the distribution of fatigue in the farms, which will reduce the frequency of maintenance and extend their life. Transport optimization for offshore wind farms can be analyzed under transport strategies [92], maintenance management and maintenance organization models. [PERSON] et al. [124] present a forecasting model for parts of an offshore wind farm, and this strategy is used to improve the availability and maintenance. Lost turbine availability is related to the failure of a component, but also depends largely on access to the turbine, and in [125], a computational approach based on probability calculations is developed, allowing estimates to be made on very fast offshore access probabilities and expected delays. Furthermore, [PERSON] et al. [126] performed research on the modeling and prediction of wave height, which is one of the key criteria for access to offshore wind farms, and this was done through data mining. The paper [127] presents an analysis of the windows of access to offshore wind farms for performing maintenance on the coasts of Ireland and Portugal, concluding that the implications of these low levels of access suggest that maintenance of power converter waves on the west coast may not be feasible and devices must be brought ashore for activities of O&M. There are proposals to improve the maintenance of wind farms, such as opportunistic maintenance policies [107], with which optimization of these tasks is intended. The research work [80] aims to optimize maintenance by using the stochastic model, since wind turbines have a more complex process of degradation than equipment working under stationary conditions.