Supervisory Controller for smoothing WindTurbine power output based on FESS using ANNs for short-term ahead prediction Academic Article in Scopus uri icon

abstract

  • © 2018 IEEE.One of the most challenging aspects concerning the increasing penetration ofEolic generation isthe highly uncertain nature ofwind,whichmaybethe origin of several problems related with output power quality, system stability and poor reliability ofwind energy generation. Include an Energy Storage System (ESS)isa common solution to mitigate the negative effectsof power fluctuation in renewable generators. Theuse of Flywheels Energy Storage Systems (FESSs)isan attractive solution inwind applications. This paper presents afuzzylogic supervisory controller for management stored energy inaFESS . The controller inputs are the extracted windpower,the rotational speed ofthe FESS and a predicted slope angle of the wind profile obtained using Artificial Neural Networks (ANNs).The results verify the effectiveness ofthe proposed supervisory controller by comparing the mean and standard deviation of the simulation output power against the most popular fuzzylogic controller.

publication date

  • December 26, 2018