Loss Minimization Control for Induction Generators in Wind Power Systems Using Support Vector Regression

In this paper, a novel algorithm for increasing the steady state efficiency during light load operation of the induction generator that integrated with a wind power generation system is presented. The proposed algorithm based on the flux level reduction, where the flux level is estimated using Support-Vector -Machines for regression (SVR) for the optimum d-axis current of the generator. SVR is trained off-line to estimate the unknown mapping between the system's inputs and outputs, and then is used online to calculate the optimum d-axis current for minimizing generator loss. The experimental results show that SVR can define the flux-power loss accurately and determine the optimum d-axis current value precisely. The loss minimization process is more effective at low wind speed and the percent of power saving can approach to 40%.