A nonlinear generalized predictive control for pumped storage unit

Chaoshun Li, Yifeng Mao, Jiandong Yang, Zanbin Wang and Yanhe Xu

Renewable Energy, 2017, vol. 114, issue PB, 945-959

Abstract: In this paper, the control problem of pumped storage unit (PSU) has been studied. A nonlinear generalized predictive control (NGPC) method has been applied to design the controller for a PSU. The NGPC controller is designed based on instantaneous linearization model of the control system, and the parameters of the linearized model are identified online by the recursive least square method (RLSM). Besides, in order to minimize the modelling error on initial state, a prior-knowledge learning method has been proposed to get the initial parameters for control model estimation. To verify the effectiveness of the NGPC controller, we chose a pumped-storage hydropower plant in China as the experimental subject and the simulation experiments respect to the control system are designed. The processes of start-up and speed disturbance under no-load condition have been simulated to testify the robustness and efficiency of the NGPC controller. Comparative experiments have been conducted, while the NGPC controller, a PID controller and a fractional order PID (FOPID) controller have been compared. Experimental results show that the designed NGPC could effectively restrain the oscillation of rotational speed in different working conditions of PSU and demonstrates higher robustness and stability than both the PID and FOPID controllers.

Keywords: Pumped storage unit; Pump-turbine governing system; Nonlinear generalized predictive control; Recursive least square method; Prior-knowledge learning (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (21)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:114:y:2017:i:pb:p:945-959

DOI: 10.1016/j.renene.2017.07.055

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