Artificial Intelligence for Renewable Energy Systems. Группа авторов

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Название Artificial Intelligence for Renewable Energy Systems
Автор произведения Группа авторов
Жанр Программы
Серия
Издательство Программы
Год выпуска 0
isbn 9781119761716



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selected as state variable (i.e., independent variable). Hence, the voltage-current relation of machine in matrix form is expressed as follows:

      where

      [v] = [vq1, vd1, vq2, vd2, vKq, vfr, vKd]T

      [i] = [iq1, id1, iq2, id2, iKq, ifr, iKd]T

      [z] is the impedance matrix defined in the Appendix.

      where matrix elements are explained in the Appendix.

image

      whereas β shows the phase difference between the terminal voltage of phases a and x. Numerically, the numerical value of both α and β is 30° electrical.

      The linearized version of above of nonlinear differential equation (1.45) with suitable approximation (cosΔδk = 1 and sinΔδk = Δδk) results in

      Inverse transformation of above equation yields

      where Fr and Fe represent the d-q performances indices under steady state.

      (1.48)image

      (1.49)image

      (1.50)image

      and is rearranged as

      (1.51)image

      Simplified version of above equation can be written as

image

      where

image

      In above linearized model of machine, the effect of mutual coupling between stator winding sets abc and xyz is considered (by using mutual leakage reactance, xlm and xldq). Results are presented in consideration of the asymmetrical six-phase synchronous machine (α = 30° electrical) in comparison with its three-phase equivalent.