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In this paper, a novel method is introduced for optimum energy harvest from wind farms. In the proposed method, wind farm is modeled by fuzzy-logic and the model is updated using a combination of wind parameters history and wind’s spatial information. Utilizing this model, the parameters for the wind blowing through each turbine in the wind farm is estimated. To evaluate the performance of the proposed method two practical wind types are simulated. In the first scenario, the wind maintains low turbulence and its parameters change slowly while in the second scenario the wind demonstrates high turbulences and its parameters undergo sudden shifts. Simulation results for the proposed method are obtained in both scenarios. For the first scenario, the comparison reveals that the proposed method improves the accuracy of wind speed estimation and the monotonousness of the obtained electrical voltage by 5.3% and 0.52 volts respectively compared to existing methods. These improvements reach 17.1% and 12.7 volts in the presence of high turbulence winds in the second scenario. Based on these corroborating simulations, it is concluded that the proposed method provides a more accurate estimate of wind parameters for the wind blowing through the wind farm.

Keywords: Wind Farm, Estimation of Wind Parameters, Optimum Electrical Energy, Fuzzy Modeling, Entropy

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