DOI: 10.5176/ 978-981-07-7531-5_PEEE.15

Authors: Jun-Zhe Yang, Ching-Jung Liao and Chun-Feng Lin


Correct models and parameters for a generator unit are very important because that directly influences the quality of transient, dynamic, and steady state simulations. In Taiwan power system, some generator units are too old to find the records of the parameters and some units have been upgraded by changing the excitation system so that the features and parameters are totally different from the original. If we keep using out of date models and parameters, the wrong simulation results and wrong decisions will be the consequences. Therefore, generator model parameters testing and validation is a very important subject. By the specific tests for generator unit, a part of the parameters can be calculated, but still some parameters have to be estimated by manually tuning parameters and doing curve fitting simulations. This is a time consuming task, because it is very complex to decide the parameters of generator unit. Therefore, in this paper, we applied particle swarm optimization (PSO) algorithm to estimate parameters and provided test results to verify its performance.

Keywords: particle swarm optimization algorithm, generator model parameters estimation, and curve fitting


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