Gong, X., 2019. Optimization of the power generation control process of hydraulic turbine set based on the improved BFO-PSO algorithm. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 227–231. Coconut Creek (Florida), ISSN 0749-0208.
In light of the problem that it is hard to analyze the non-linear and time-varying model in the traditional hydro-generator system identification, based on the PID control parameters, this paper proposes a hydro-turbine governing system using the improved BFO-PSO algorithm, and introduces the sliding mode variable structure into the proposed improved governing system. The research results show that: the proposed BFO-PSO model has integrated the advantages of the two algorithms and has been successfully applied in the parameter optimization of the hydraulic turbine set. This paper also studies the selection of indices for optimization of PID parameters. Considering the deficiencies in the PID parameters in previous research, this paper proposes an improved fitness evaluation method, and also puts forward the concepts of stability and instability parameter sets and applies them in the stable search strategy, which effectively improves the local search capability of the model algorithm, and guarantees the stability and accuracy of the hydro-generator model. The design of multi-control-input hydro-turbine state equations can effectively solve the steady-state errors in the simulation process and explain the generation mechanism of such errors. The simulation results show that the optimization result of this algorithm significantly shortens the ITAE transition rising time of the hydro-turbine set and that the target population has been moving towards the global optimal solution, thus increasing the searching ability of the algorithm. The curve fluctuates slightly and reaches the steady state in a very short time.