Optimization to POD parameters of DFIGs based on the 2nd order eigenvalue sensitivity of power systems

Abstract

Here, the analytical model of the 2nd order eigenvalue sensitivity is improved, and applied to optimize the parameters of the power oscillation dampers of the doubly‐fed induction generators. To solve the 2nd order eigenvalue sensitivity, the eigenvector sensitivity is required whose difficulty lies in insufficient constraints, for which two constraints about the magnitude and the angle of eigenvector elements are newly introduced, and the normalization conditions are derived to solve the eigenvector sensitivity. The 2nd order eigenvalue sensitivity is applied to analyse the change of the low‐frequency oscillation modes with the varying of parameters in the power systems with the doubly‐fed induction generators. To improve the low‐frequency oscillation modes, the optimization model of the power oscillation damper parameters is newly formulated based on the 1st and the 2nd order eigenvalue sensitivities and solved by the interior point method. The numerical results are provided to verify the effectiveness of the constraints proposed; the advantages of the 2nd order eigenvalue sensitivity in the eigen‐analysis and parameters optimization, and the robustness against wind fluctuation.

Eigen-Sensitivity-Based Sliding Mode Control for LFO Damping in DFIG-Integrated Power Systems

“…The control parameters are gradually changed to draw the locus of the LFO modes to verify the control effect. It is computationally expensive since each time only one parameter is checked [26]. Sensitivities of eigenvalues are more effective to decide the control effect [27].…”

“…Multiplying a complex number k∠θ to both sides of ( 26), one obtains (28). It can be found that the eigenvectors corresponding to different k and θ satisfy (26). Hence, for each eigenvalue, there are numerous eigenvectors, as shown in Figure 5.…”