An efficient numerical method for computing eigenvalue sensitivity with respect to operational parameters of large-scale power systems

Eigenvalue sensitivity with operational parameters provides necessary information for tuning power system operating status and improving small signal stability. Presently, with the inter-connection of regional power grids, power systems expand to be of large scale, which raises demanding requirements for computational efficiency of eigenvalue sensitivity analysis. For addressing this issue, a modified numerical method is proposed for computing eigenvalue sensitivity with respect to power system operational parameters, including active and reactive power outputs of generation units, load demands and bus voltages. Well computational efficiency is obtained by the proposed method, which is mainly attributed to the reuse of LU factorization in solving perturbed power flow equations, the numerical finite difference for evaluating state matrix sensitivity, and utilization of parallel computing techniques. Numerical experiments on different scale power systems from realistic world are performed to validate its effectiveness and efficiency. Parallelization of the proposed method is implemented for further reducing overall time cost. Moreover, the proposed method is integratable to functional modules of existing power system analysis software, which makes its implementation convenient.