Abstract: Small signal stability causes small perturbations in the
generator that can cause instability in the power network. It is
generally known that small signal stability are directly related to the
generator and load properties. This paper examines the effects of
generator input variations on power system oscillations for a small
signal stability study. Eigenvaules and eigenvectors are used to
examine the stability of the power system. The dynamic power
system's mathematical model is constructed and thus calculated using
load flow and small signal stability toolbox on MATLAB. The power
system model is based on a 3-machine 9-bus system that was
modified to suit this study. In this paper, Participation Factors are a
means to gauge the effects of variation in generation with other
parameters on the network are also incorporated.
Abstract: Genetic algorithms (GAs) have been widely used for
global optimization problems. The GA performance depends highly
on the choice of the search space for each parameter to be optimized.
Often, this choice is a problem-based experience. The search space
being a set of potential solutions may contain the global optimum
and/or other local optimums. A bad choice of this search space
results in poor solutions. In this paper, our approach consists in
extending the search space boundaries during the GA optimization,
only when it is required. This leads to more diversification of GA
population by new solutions that were not available with fixed search
space boundaries. So, these dynamic search spaces can improve the
GA optimization performances. The proposed approach is applied to
power system stabilizer optimization for multimachine power system
(16-generator and 68-bus). The obtained results are evaluated and
compared with those obtained by ordinary GAs. Eigenvalue analysis
and nonlinear system simulation results show the effectiveness of the
proposed approach to damp out the electromechanical oscillation and
enhance the global system stability.