Identification of main steam temperature of power plant using fractional-order transfer function based on Lévy flights — Artificial bee colony algorithm

Fractional-order calculus with special memorability could describe dynamic characteristics of the object more accurately, and the establishment of fractional-order mathematical model can provide more convenience for tuning the parameters of PI
^λ
D
^μ
controller. Fractional-order transfer functions can completely represent characteristics of thermal process compared with the integral-order ones applied in coal-fired power plant, such as strong coupling, disturbance factors, huge difference between response speed, etc. Aiming at the characteristics of multiple parameters for fractional-order transfer function model, two promising approaches are proposed. Firstly, an improved artificial bee colony algorithm, based on Lévy flights strategy, is introduced in optimizing the parameters of nominal model. Secondly, objective (fitness) function with penalty factor is developed to obtain the static gain of model. Finally, it is attempted to apply the proposed identification method, based on fractional-order transfer function model, to a circulating fluidized bed (CFB) superheater in an in-service power unit. The field data identification well demonstrates the virtues of improved identification method and indicates promising prospects for fractional-order transfer function model in thermal process of power plant.