Evaluation of gain scheduled predictive control in a nonlinear MIMO model of a hydropower station

• Published in: International journal of electrical power & energy systems 2015-03, Vol.66, p.125-132
• Main Authors: Munoz-Hernandez, G.A., Gracios-Marin, C.A., Jones, D.I., Mansoor, S.P., Guerrero-Castellanos, J.F., Portilla-Flores, E.A.
• Format: Article
• Language: English
• Subjects: Computational efficiency; Gain; Hydroelectric power stations; Mathematical models; Modeling; Multivariable control systems; Nonlinearity; Performance evaluation; Piecewise systems; Power plants; Power stations control; Predictive control
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2014.10.008

•Nonlinear modeling of a hydroelectric pumped-storage station.•Hybrid reduced order model of a hydroelectric pumped-storage station.•Evaluation of Gain Scheduling Predictive Controller in a hydropower station model. This work deals with the evaluation of the performance of a predictive control applied to a nonlinear model of Dinorwig a pumped storage hydropower plant. The controller uses a piecewise-linear plant model for prediction and is gain-scheduled according to the number of active hydro-generation Units (ranging from 1 to 6). Simulated results are presented to evaluate the performance of the predictive controller, which is compared with a gain-scheduled PI controller that has anti-windup features; this controller was tuned using the current practical values. The results show that the response, to various changes in the plant operating conditions, obtained with the predictive controller is faster and less sensitive than the one obtained from the PI controller. The results also show how reduced-order models can be used for prediction, allowing the reduction of the computing time (or the computing cost) without compromising the closed-loop performance control signal.