Full Operational Envelope Control of a Wind Turbine Using Model Predictive Control

Abstract

This study presents a full operational envelope controller for a full nonlinear 5 MW Supergen exemplar wind turbine based on multivariable model predictive control (MPC). Below the rated wind speed, the primary objective of the controller is to maximize the energy capture. Above the rated wind speed, the controller maintains the rated power. The controller switches between control modes according to the prevailing wind speed to maintain control over the full envelope of operating regions. A linearized model is derived from a model of an exemplar 5 MW Supergen wind turbine in state-space form. The linearized model is then used to realize a feedback MPC (FB-MPC) and feedforward MPC (FF-MPC) to consider the lack and incorporation, respectively, of wind speed information. The switching strategy is tracked on the torque-speed plane. Simulations are performed at multiple wind speeds to evaluate the robustness and switching performances of the designed controllers by applying them to a full nonlinear 5 MW Matlab/SIMULINK model of the same exemplar Supergen wind turbine. Improved tracking is achieved over the full envelope with FF-MPC rather than FB-MPC. Simulation results are presented in the time and frequency domain in addition to the torque-speed plane demonstrating that the control performance is improved without an increase in the control activity (i.e., pitch action) of the turbine; that is, the controller's gain crossover frequency remains within the acceptable range, around 1 rad/s. Note that most work presented in the literature focus on specific wind speeds only; that is, either only below rated wind speed or above rated wind speed. In contrast, the controllers reported here cover the full envelope of operation regions, making this work more practical and novel. INDEX TERMSwind turbine, modeling, predictive control, feedforward control I. INTRODUCTION Wind power has been one of the fastest-growing sustainable energy sources in the past few decades. According to the Global Wind Energy Council [1], >740 GW of wind energy is installed worldwide. Variable-speed wind turbines are designed to operate across a large range of wind speeds of 4-25 m/s [2], [3]. The control of such turbines is partitioned into several modes depending on the prevailing wind speed: (I) The turbine is idle owing to a lack of sufficient wind. (II) The rotor speed of the turbine is varied to maximize the rotor efficiency at a fixed blade pitch.(III) The generator speed is at its maximum, but the generated power is below the nominal value. (IV) The generator torque is fixed, and the blade pitch is varied to compensate for the variation in wind power.

A Comparative Study of Optimal Individual Pitch Control Methods

“…The H ∞ -based control could suffer from being mathematically complex, being generally of a high order which makes its usage difficult in practical applications [42]. Since a linearised model is taken for the controller design, it can exhibit model-plant mismatch when applied to a real-life turbine [24,30]. MPC-based control has the disadvantage of requiring an accurate mathematical model of the system dynamics.…”

“…Unmodelled dynamics and model uncertainties can adversely affect the performance of MPC. Another main drawback of MPC is that it could be computationally intensive, involving the solution of the optimization problem for each control action, making its application limited in practical applications [29][30][31]. Moreover, it could be sensitive to modeling errors and requires an initialization and warm-up time period to converge to optimal control actions [31].…”

“…The pitch activity increases significantly as a side effect of IPC; hence MPC based IPC controller is employed to maintain smooth pitch activity due to its inherent ability to include prediction and constraint handling. Also, the MPC application in IPC shows the capacity to reduce rotating blade loads, fixed rotor loads, and drive train loads [29][30][31][32][33]. The H ∞ -based robust control strategy is used as the controllers developed using this method have the ability to treat the unmodelled dynamics and uncertainties in the plant model [25].…”

“…Subsequently, other advanced optimal controllers, like model predictive controllers (MPCs), have also been employed for IPC design [29][30][31][32]. The pitch activity increases significantly as a side effect of IPC; hence MPC based IPC controller is employed to maintain smooth pitch activity due to its inherent ability to include prediction and constraint handling.…”

On the Regulation of Wind Energy Conversion Systems Working as Conventional Generation Plants

“…Nonetheless, it has been argued that renewable energy sources are of utmost importance for environmental and economic reasons [2][3][4]. In particular, wind power has proven to be an ecologically viable alternative for electric generation, with a continuously increasing installed capacity year after year [5]. The year 2020 was a notoriously positive period in the global wind industry, with a year-on-year growth of 53%, and more than 93 GW of wind power installed [6].…”