A nonlinear generalized predictive control for pumped storage unit

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 pa...

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Published inRenewable energy Vol. 114; pp. 945 - 959
Main Authors Li, Chaoshun, Mao, Yifeng, Yang, Jiandong, Wang, Zanbin, Xu, Yanhe
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.12.2017
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ISSN0960-1481
1879-0682
DOI10.1016/j.renene.2017.07.055

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Summary: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. •In this paper, the nonlinear predictive control of a pumped storage unit has been studied.•The nonlinear controller is designed based on instantaneous linearization and online identification by the RLSM.•A prior-knowledge learning method has been proposed to initial the control model estimation.•The processes of start-up and speed disturbance under no-load condition have been simulated.
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ISSN:0960-1481
1879-0682
DOI:10.1016/j.renene.2017.07.055