The use of a model independent control approach to tackle the problem of wind farm power maximization under constant and varying free stream wind speed and direction is considered. In this paper, a time-varying extremum seeking control (TVESC) for discrete-time systems is utilized in a distributed and a collaborative manner. Each controller monitors the actions of a wind turbine and the objective is to maximize the farm wide power capture. To address this task, the distributed controllers ensure that the turbines share local information over an undirected connected communication network. Also, with the use of a discretized version of a continuous-time dynamic average consensus estimator, the controllers help the turbines estimate the mean of the overall power generated in the wind farm. The dynamics of each turbine power estimate is parameterized and the unknown gradient is estimated as a time-varying parameter using a tailored estimation routine. This information is used in the design of the extremum seeking controller. The problem to be solved is addressed via numerical simulations, results are provided to show the effectiveness of this technique.
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