AVR and PSS Coordination Strategy by Using Multi- objective Ant Lion Optimizer (CROSBI ID 706792)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Špoljarić, T. ; Pavić, I.
engleski
AVR and PSS Coordination Strategy by Using Multi- objective Ant Lion Optimizer
In this paper a novel optimization method called Multi-Objective Ant Lion Optimizer (MOALO) is proposed for tuning synchronous generator excitation controls in multi machine power system. Devices used in excitation control are automatic voltage regulator (AVR) and power system stabilizer (PSS). Two area four machine model (TAFM) is used for observing power system dynamics through several various operating states. In a performance analysis of a proposed algorithm two objective functions are used. First objective function uses integral of time weighted absolute error of rotor speed, voltage and tie line active power data, while second objective function uses mean value of time domain transitional process quality indicators such as overshoot, undershoot and settling time. A proposed algorithm is tested and its performance is compared with performances of two other multi objective swarm intelligence algorithms: Multi- Objective Particle Swarm Optimization (MOPSO) and Multi-Objective Salp Swarm Algorithm (MOSSA). Results are compared and presented as sets of solutions composed in Pareto fronts.
Generator Excitation Controls ; Multi-objective optimization ; Ant Lion Optimizer ; Power System Dynamics
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Podaci o prilogu
1151-1156.
2020.
objavljeno
10.23919/mipro48935.2020.9245128
Podaci o matičnoj publikaciji
IEEE Xplore - 2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO)
Institute of Electrical and Electronics Engineers (IEEE)
2623-8764
Podaci o skupu
MIPRO 2020
predavanje
28.09.2020-02.10.2020
Opatija, Hrvatska