Coordinated Design of Multiple Damping Controllers based on Computational Intelligence

Q. Sun, Y.-Y. Wang, and C. Chen (PRC)


Damping control, Genetic algorithms, Low-frequency oscillation, Ordinal optimization, Robust decentralized control.


This paper presents a global tuning procedure for FACTS damping controllers and power system stabilizers in a multi-machine power system, based on computational intelligence combining ordinal optimization (OO) with genetic algorithms (GA). The main objective of this procedure is to simultaneously optimize parameters of multiple damping controllers in a robust manner. Considering the relation between the trace of a matrix and its eigenvalues, a criterion function is defined, which can be easily computed and utilized to evaluate the performance of solutions approximately. Thus the fitness of individuals in GA is determined based on ordinal comparison of performance using OO method. Together with linear ranking selection operator, it can dramatically shorten the search process with less computation burden and higher efficiency. The tuning procedure is applied to the well-known New England system and the simulation results validate the effectiveness and robustness of the coordinated design method presented.

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