Abstract

Wind power generation has undergone significant development in recent decades due to its environmental advantages and its economic competitiveness. However, its increasing level of penetration is not exempt from drawbacks, such as those derived from the fluctuating nature of the wind. To reduce its negative incidence on grid power quality and stability, different techniques have been developed, such as those based on power smoothing. In these techniques, there is a research gap on the adjustment of the time constant that adapts to the needs of the smoothing, avoiding uncertain results, computational efforts and delays in the response of the control. This paper addresses the problem, proposing a novel method for power smoothing in a wind turbine by using a fuzzy-logic-based supercapacitor storage system and time-constant fitting, with a first-order adaptive transfer function. The method considers as input variables the active power generated by the wind turbine and the state of charge of the supercapacitor, both sampled simultaneously. After a computation process, the proposal generates active power set-point values that the supercapacitor must produce to compensate for the intermittency of the wind, seen from the point of connection to the grid. The results were validated experimentally with comprehensive laboratory tests.

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