Turkish Journal of Electrical Engineering and Computer Sciences
DOI
10.3906/elk-1305-114
Abstract
Power line parameters are an important factor in relay applications and power quality studies. In the literature, the phasor measurement unit method and measuring of current and voltage at two ends of the power line were usually used to estimate the power line parameters. In this study, the parallel resonance impedance detection method was used to estimate the power line parameter to obtain input data. The real measurement values are used to obtain parallel resonance impedance in this method. The real measurement values include the measurement errors of the current and voltage transformer. Thus, the estimated parameter values are realistic. The electrical network with has 27 busbars that belongs to an organized industrial zone in Turkey was used for the application. Harmonic measurement of the power line of the electrical network was made to obtain parallel resonance impedance. The obtained parallel resonance impedance was used in the maximization problem. The maximization problem was defined as the estimated accuracy rate and was solved by using the clonal selection algorithm, genetic algorithm, and particle swarm optimization to make the most realistic parameter estimation. These methods can be defined as parameter estimators and are selected because they are all used widely in electrical engineering problem solutions. The results of these methods were compared with real parameter values, and accuracy of the estimate was determined for each method.
Keywords
Clonal selection algorithm, electric network, genetic algorithm, particle swarm optimization, parallel resonance impedance, parameter estimation, power line
First Page
12
Last Page
23
Recommended Citation
AKBAL, BAHADIR and ÜRKMEZ, ABDULLAH
(2016)
"The parallel resonance impedance detection method for parameter estimation of power line and transformer by using CSA, GA, and PSO,"
Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 24:
No.
1, Article 2.
https://doi.org/10.3906/elk-1305-114
Available at:
https://journals.tubitak.gov.tr/elektrik/vol24/iss1/2
Included in
Computer Engineering Commons, Computer Sciences Commons, Electrical and Computer Engineering Commons