Genetic-based algorithm for identification of synchronous machine parameters using short-circuit tests

In this paper a new method for the digital identification of synchronous machine parameters from short-circuit tests is presented. The method is based on the genetic algorithm optimization technique. Genetic algorithms (GAs) are adaptive search procedures based on the mechanism of natural selection and genetics. This kind of algorithm can search for a global solution using multiple paths. The proposed method uses a digital set of measurements for the short-circuit current for estimating direct axis reactance and time constant. A set of over-determined system of equations is constructed using the digital current samples. The identification problem is then solved using the proposed GAs-based method. Different fitness functions that evaluate the solutions are suggested. A practical case study is presented in this work to evaluate the proposed method. Results are reported and conclusions are drawn.