TY - JOUR
T1 - Analysis of small signal stability margins using genetic optimization
AU - Dong, Zhao Yang
AU - Makarov, Yuri V.
AU - Hill, David J.
N1 - Funding Information:
This work was sponsored by the ERDC/ESAA Research Program Contract PN2420/94120. Z.Y. Dong’s work was supported by Sydney University Electrical Engineering Postgraduate Scholarship. The authors would like to thank Mr Haining Liu of Tianjin University for his helpful discussion on GAs.
PY - 1998/9/1
Y1 - 1998/9/1
N2 - 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 power system parameters of interest, including load flow feasibility, saddle node and Hopf bifurcation ones; (2) finding the maximum and minimum damping conditions; and (3) determining control actions to provide and increase small signal stability. These problems are presented in this paper as different modifications of a general optimization to a minimum/maximum, depending on the initial guesses of variables and numerical methods used. In the considered problems, all the extreme points are of interest. Additionally, there are difficulties with finding the derivatives of the objective functions with respect to parameters. Numerical computations of derivatives in traditional optimization procedures are time consuming. In this paper, we propose a new black-box genetic optimization technique for comprehensive small signal stability analysis, which can effectively cope with highly nonlinear objective functions with multiple minima and maxima, and derivatives that can not be expressed analytically. The optimization result can then be used to provide such important information such as system optimal control decision making, assessment of the maximum network's transmission capacity, etc.
AB - 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 power system parameters of interest, including load flow feasibility, saddle node and Hopf bifurcation ones; (2) finding the maximum and minimum damping conditions; and (3) determining control actions to provide and increase small signal stability. These problems are presented in this paper as different modifications of a general optimization to a minimum/maximum, depending on the initial guesses of variables and numerical methods used. In the considered problems, all the extreme points are of interest. Additionally, there are difficulties with finding the derivatives of the objective functions with respect to parameters. Numerical computations of derivatives in traditional optimization procedures are time consuming. In this paper, we propose a new black-box genetic optimization technique for comprehensive small signal stability analysis, which can effectively cope with highly nonlinear objective functions with multiple minima and maxima, and derivatives that can not be expressed analytically. The optimization result can then be used to provide such important information such as system optimal control decision making, assessment of the maximum network's transmission capacity, etc.
KW - Bifurcations
KW - Genetic algorithms
KW - Power system security
KW - Stability
UR - https://www.scopus.com/pages/publications/0032157393
U2 - 10.1016/s0378-7796(98)00009-1
DO - 10.1016/s0378-7796(98)00009-1
M3 - Article
AN - SCOPUS:0032157393
SN - 0378-7796
VL - 46
SP - 195
EP - 204
JO - Electric Power Systems Research
JF - Electric Power Systems Research
IS - 3
ER -