Design and implementation of a fuzzy controller for wind generators performance optimisation Vito Calderaro, Vincenzo Galdi, Antonio Piccolo, Pierluigi Siano DIIIE, UNIVERSITY OF SALERNO Fisciano, (SA) Italy Tel.: +39/089964294 Fax: +39/089964284 E-Mail: vcalderaro@unisa.it;vgaldi@unisa.it, apiccolo@unisa.it; psiano@unisa.it URL: http://www.unisa.it/Dipartimenti/DIIIE Keywords «Fuzzy control», «Wind energy», «Adaptive control», «Power supply». Abstract Actual wind power costs together with incentives and financing options for developing renewable energy facilities make wind energy source competitive with conventional generation sources and it is believed that wind energy will be the most cost effective source of electrical power in the next future. However, the wind power production diffusion involves the development of efficient control systems able to improve wind systems effectiveness. Therefore, a design methodology, able to generate an adaptive fuzzy model for maximum energy extraction from variable speed wind turbines is proposed in this paper. The fuzzy model is designed by using fuzzy clustering combined with genetic algorithms (GA) and recursive least- squares (LS) optimisation methods. Some simulation results on a doubly-fed induction generator confirmed that the proposed design methodology is able to identify a Takagi-Sugeno-Kang (TSK) fuzzy model exhibiting adaptivity, learning capability, high speed of computation and low memory occupancy. Introduction Wind energy represents a renewable natural energy resource which can provide a considerable effort to electricity production, allowing a reduction of the environmental impact because of its feature of generating carbon-emission-free electricity. Therefore, nowadays many European countries energy policies have the purpose to enhance wind energy utilization, also by means of incentives and financing options [1]. In order to establish wind energy expansion, the development of efficient control systems, that can improve the wind systems effectiveness, is essential. Wind turbines can operate at fixed speed or variable speed, however variable speed operation is preferable as it allows a reduction of the mechanical structure stresses and the acoustic noise and the control of active and reactive power. Moreover, variable speed operation increases the energetic efficiency and reduces the drive train torque and generated power fluctuations [2]. Because the effectiveness of control systems for variable speed wind turbines is fundamental and, considering that fuzzy control can offer many advantages over traditional controls, such as fast convergence, adaptivity and parameter insensitiveness [3], a sensorless peak power tracking adaptive fuzzy control for variable speed wind turbines is proposed in this paper. The proposed adaptive fuzzy control is able to counterbalance the non-linearities and time variances of the system under control by means of its adaptability and learning capability. In fact, even if a linear controller is designed using realistic and accurate simulation models described in terms of transfer functions, simulated systems don’t describe a wind turbine to its full extent [4] and it is probable that the controller would need further adjustments before it can be applied in a real wind turbine. Authorized licensed use limited to: Universita degli Studi di Salerno. Downloaded on June 10,2010 at 14:51:20 UTC from IEEE Xplore. Restrictions apply.