Improvement of Identification Procedure Using Hybrid Cuckoo Search Algorithm for Turbine-Governor and Excitation System

In this paper, a new method is introduced in order to modify identification process of a gas power plant using a meta-heuristic algorithm named Cuckoo Search (CS). Simulations play a significant role in dynamic analyses of power plants. This paper points out to a practical approach in model selection and parameter estimation of gas power plants. The identification and validation process concentrates on two subsystems: governor-turbine and exciter. Standard models GGOV1 and STB6 are preferred for the dynamical structures of governor-turbine and exciter, respectively. Considering definite standard structure, main parameters of dynamical model are pre-estimated via system identification methods based on field data. Then obtained parameters are tuned carefully using an iterative Cuckoo algorithm. Models must be validated by results derived via a trial and error series of simulation in comparison to measured test data. The procedure gradually yields in a valid model with precise estimated parameters. Simulation results show accuracy of identified models. Besides, a whiteness analysis has been performed in order to show the authenticity of the proposed method in another way. Despite various detailed models, practical attempts of model selection, identification, and validation in 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 chosen as a benchmark for model validation.