1 research outputs found
Improvement of Identification Procedure Using Hybrid Cuckoo Search Algorithm for TurbineGovernor and Excitation System
In this paper a new method is introduced in order to modify identification
process of a gas power plant using a metaheuristic 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.Comment: 10 pages, 9 figures, 3 tables, Published in: IEEE Transactions on
Energy Conversio