Saudi Journal of Engineering and Technology (SJEAT)
Volume-2 | Issue-11 | 419-427
Review Article
Robust control of Multi Machine Power System Using Intelligent Control methods and their Performance Comparison
Abdul Hameed Kalifullah, Sankaran Palani
Published : Nov. 30, 2017
Abstract
This paper is deals with the robustness property of various intelligent
control methods namely Genetic Algorithm (GA), Particle Swarm Optimization
(PSO), Bacterial Foraging Algorithm (BFA), and Harmony Search Algorithm (HSA)
for the design of Power system stabilizer for multi machine power system. The
problem of robustly tuning of PID based stabilizer design is formulated as an
optimization problem according to the time domain-based objective function with
some performance indices which is solved by intelligent control methods that have a
strong ability to find the most optimistic results. To demonstrate the effectiveness and
robustness of the proposed stabilizers, the design process takes a wide range of
operating conditions and system configuration into account. The comparison is
carried out in terms of robustness, peak over shoot and settling time of the system
dynamic response. For completeness, the performance of conventional controllers is
also included. The results of these studies show that the proposed intelligent control
methods based PID type stabilizers have an excellent capability in damping power
system oscillations and enhance greatly the dynamic stability of the power system in
addition to maintaining robustness for a wide range of loading conditions.