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Controller parameter tuning of a single machine infinite bus system with static synchronous compensator using antlion optimization algorithm for the power system stability improvement
Author(s) -
Devarapalli Ramesh,
Bhattacharyya Biplab,
Saw Jitendra Kumar
Publication year - 2020
Publication title -
advanced control for applications: engineering and industrial systems
Language(s) - English
Resource type - Journals
ISSN - 2578-0727
DOI - 10.1002/adc2.45
Subject(s) - control theory (sociology) , benchmark (surveying) , particle swarm optimization , electric power system , stability (learning theory) , controller (irrigation) , static var compensator , power (physics) , oscillation (cell signaling) , engineering , computer science , control engineering , algorithm , control (management) , physics , quantum mechanics , artificial intelligence , machine learning , agronomy , biology , genetics , geodesy , geography
The improvement of power system stability by damping oscillations in the system states is presented in this paper. An antlion optimization (ALO) algorithm is adopted to tune the damping device controller parameters. The ALO algorithm performance is investigated on the benchmark functions, and the same has been compared with the traditional particle swarm optimization (PSO) technique. The statistical analysis on the fitness achieved with the considered algorithms has been demonstrated using best, worst, mean, and SD values on the benchmark functions over 30 individual runs. Here power system stabilizer (PSS) and static synchronous compensator are considered as oscillation damping devices in the test power network. The analysis has been carried out in a sample power system network, and the proposed technique is compared with the conventional PSS and PSO. The results obtained from the designed test system recommends the superior performance characteristics of ALO in applying to the practical power system.