Generator Excitation System Parameter Identification and Tuning by Using PSO

This paper presents the optimization technique for generator excitation system parameter identification as well as parameter tuning by using Particle Swarm Optimization (PSO) associated with the curve fitting function. The actual measurement signal is used as the reference signal in the optimization...

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Bibliographic Details
Published in2019 7th International Electrical Engineering Congress (iEECON) pp. 1 - 4
Main Authors Kittiwattanaphon, Sapanan, Wangdee, Wijarn, Katithummarugs, Siriporn
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2019
Subjects
Curve fitting
excitation system
Generators
Matlab
microgrid
optimal tuning
Optimization
Parameter estimation
parameter identification
particle swarm optimization
Power system dynamics
Tuning
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Summary:This paper presents the optimization technique for generator excitation system parameter identification as well as parameter tuning by using Particle Swarm Optimization (PSO) associated with the curve fitting function. The actual measurement signal is used as the reference signal in the optimization process. The dynamic performance is then enhanced by tuning the parameters using the desired reference signal created to comply with the power utility criteria. The co-simulation process between MATLAB and DIgSILENT software is applied for the proposed optimization process. The results indicate that the proposed technique can optimize the parameters that are well performed when the generator is disconnected from the main grid and runs as a microgrid operation. The results are demonstrated using the actual power distribution system located in Thailand.
DOI:10.1109/iEECON45304.2019.8939048