Abstract
The static synchronous compensator (STATCOM) is the multipurpose FACTS
device with the multiple input and multiple output system for the
enhancement of its dynamic performance in power system. Based on
artificial intelligence (AI) optimization technique, a novel controller is
proposed for CSC based STATCOM. In this paper, the CSC based STATCOM is
controlled by the LQR. But the best constant values for LQR controller's
parameters are obtained laboriously through trial and error method,
although time consuming. So the goal of this paper is to investigate the
ability of AI techniques such as genetic algorithm (GA) and particle swarm
optimization (PSO) methods to search the best values of LQR controller's
parameters in a very short time with the desired criterion for the test
system. Performances of the GA, PSO & ABC based LQR controllers are also
compared. Applicability of the proposed scheme is demonstrated through
simulation in MATLAB and the simulation results are shown an improvement
in the input-output response of CSC-STATCOM.
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