10-05-2012, 03:37 PM
Robust Power System Stabilizer Design using Particle Swarm Optimization Technique
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INTRODUCTION
LOW frequency oscillations are observed when large
power systems are interconnected by relatively weak tie
lines. These oscillations may sustain and grow to cause
system separation if no adequate damping is available [1].
Power system stabilizers (PSS) are now routinely used in the
industry to damp out oscillations. An appropriate selection of
PSS parameters results in satisfactory performance during
system disturbances [2].
The problem of PSS parameter tuning is a complex
exercise. A number of conventional techniques have been
reported in the literature pertaining to design problems of
conventional power system stabilizers namely: the eigenvalue
assignment, mathematical programming, gradient procedure
for optimization and also the modern control theory [3].
Unfortunately, the conventional techniques are time
consuming as they are iterative and require heavy computation
burden and slow convergence.
OVERVIEW OF PARTICLE SWARM OPTIMIZATION (PSO)
The PSO method is a member of wide category of Swarm
Intelligence methods for solving the optimization problems. It
is a population based search algorithm where each individual
is referred to as particle and represents a candidate solution.
Each particle in PSO flies through the search space with an
adaptable velocity that is dynamically modified according to
its own flying experience and also the flying experience of the
other particles. In PSO each particles strive to improve
themselves by imitating traits from their successful peers.
Further, each particle has a memory and hence it is capable of
remembering the best position in the search space ever visited
by it.
RESULTS AND DISCUSSIONS
The SimPowerSystems (SPS) toolbox is used for all
simulations and SSSC-based damping controller design. SPS
is a MATLAB-based modern design tool that allows scientists
and engineers to rapidly and easily build models to simulate
power systems using Simulink environment. The SPS’s main
library, powerlib, contains models of typical power equipment
such as machines, governors, excitation systems, transformers,
and transmission lines. The library also contains the Powergui
block that opens a graphical user interface for the steady-state
analysis of electrical circuits. The Load Flow and Machine
Initialization option of the Powergui block performs the load
flow and the machines initialization [11].
CONCLUSION
In this paper, power system stability enhancement by power
system stabilizer is presented. For the proposed controller
design problem, a non-liner simulation-based objective
function to increase the system damping was developed. Then,
the particle swarm optimization technique is implemented to
search for the optimal controller parameters. The effectiveness
of the both the proposed controller, for power system stability
improvement, is demonstrated by a weakly connected example
power system subjected to different severe disturbances. The
dynamic performance of proposed PSS has also been
compared with a conventionally designed PSS to show its
superiority. The non-linear simulation results presented under
wide range of operating conditions; disturbances at different
locations as well as for various fault clearing sequences, show
the effectiveness and robustness of the proposed PSO
optimized PSS controller and their ability to provide efficient
damping of low frequency oscillations.