ANALYSIS OF SMALL-SIGNAL STABILITY MARGINS USING GENETIC OPTIMIZATION

Power system small signal stability analysis aims to explore different small signal stability conditions and controls, namely: (1) exploring the power system security domains and boundaries in the space of powe r system parameters of interest, including load flow feasibility, sadd le node and Hopf bifurcation ones; (2) finding the maximum and minimum damping conditions; and (3) determining control actions to provide an d increase small signal stability. These problems are presented in thi s paper as different modifications of a general optimization to a mini mum/maximum, depending on the initial guesses of variables and numeric al methods used. In the considered problems, all the extreme points ar e of interest. Additionally, there are difficulties with finding the d erivatives of the objective functions with respect to parameters. Nume rical computations of derivatives in traditional optimization procedur es are time consuming. In this paper, we propose a new black-box genet ic optimization technique for comprehensive small signal stability ana lysis, which can effectively cope with highly nonlinear objective func tions with multiple minima and maxima, and derivatives that can not be expressed analytically. The optimization result can then be used to p rovide such important information such as system optimal control decis ion making, assessment of the maximum network's transmission capacity, etc. (C) 1998 Elsevier Science S.A. All rights reserved.