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In this paper a new method is introduced in order to modify identificationprocess of a gas power plant using a metaheuristic algorithm named CuckooSearch (CS). Simulations play a significant role in dynamic analyses of powerplants. This paper points out to a practical approach in model selection andparameter estimation of gas power plants. The identification and validationprocess concentrates on two subsystems: governor-turbine and exciter. Standardmodels GGOV1 and STB6 are preferred for the dynamical structures ofgovernor-turbine and exciter respectively. Considering definite standardstructure, main parameters of dynamical model are pre estimated via systemidentification methods based on field data. Then obtained parameters are tunedcarefully using an iterative Cuckoo algorithm. Models must be validated byresults derived via a trial and error series of simulation in comparison tomeasured test data. The procedure gradually yields in a valid model withprecise estimated parameters. Simulation results show accuracy of identifiedmodels. Besides, a whiteness analysis has been performed in order to show theauthenticity of the proposed method in another way. Despite various detailedmodels, practical attempts of model selection, identification, and validationin a real gas unit could rarely be found among literature. In this paper,Chabahar power plant in Iran, with total install capacity of 320 MW, is chosenas a benchmark for model validation.

Improvement of Identification Procedure Using Hybrid Cuckoo Search Algorithm for TurbineGovernor and Excitation System