Modelling and control of coupled infinite-dimensional systems

First, we consider two classes of coupled systems consisting of an infinite-dimensional part [sigma]d and a finite-dimensional part [sigma]f connected in feedback. In the first class of coupled systems, we assume that the feedthrough matrix of [sigma]f is 0 and that [sigma]d is such that it becomes well-posed and strictly proper when connected in cascade with an integrator. Under several assumptions, we derive well-posedness, regularity and exact (or approximate) controllability results for such systems on a subspace of the natural product state space. In the second class of coupled systems, [sigma]f has an invertible first component in its feedthrough matrix while [sigma]d is well-posed and strictly proper. Under similar assumptions, we obtain well-posedness, regularity and exact (or approximate) controllability results as well as exact (or approximate) observability results for this class of coupled systems on the natural state space. Second, we investigate the exact controllability of the SCOLE (NASA Spacecraft Control Laboratory Experiment) model. Using our theory for the first class of coupled systems, we show that the uniform SCOLE model is well-posed, regular and exactly controllable in arbitrarily short time when using a certain smoother state space. Third, we investigate the suppression of the vibrations of a wind turbine tower using colocated feedback to achieve strong stability. We decompose the system into a non-uniform SCOLE model describing the vibrations in the plane of the turbine axis, and another model consisting of a non-uniform SCOLE system coupled with a two-mass drive-train model (with gearbox), in the plane of the turbine blades. We show the strong stabilizability of the first tower model by colocated static output feedback. We also prove the generic exact controllability of the second tower model on a smoother state space using our theory for the second class of coupled systems, and show its generic strong stabilizability on the energy state space by colocated feedback

Deep neural learning based distributed predictive control for offshore wind farm using high fidelity LES data

The paper explores the deep neural learning (DNL) based predictive control approach for offshore wind farm using high fidelity large eddy simulations (LES) data. The DNL architecture is defined by combining the Long Short-Term Memory (LSTM) units with Convolutional Neural Networks (CNN) for feature extraction and prediction of the offshore wind farm. This hybrid CNN-LSTM model is developed based on the dynamic models of the wind farm and wind turbines as well as higher-fidelity LES data. Then, distributed and decentralized model predictive control (MPC) methods are developed based on the hybrid model for maximizing the wind farm power generation and minimizing the usage of the control commands. Extensive simulations based on a two-turbine and a nine-turbine wind farm cases demonstrate the high prediction accuracy (97% or more) of the trained CNN-LSTM models. They also show that the distributed MPC can achieve up to 38% increase in power generation at farm scale than the decentralized MPC. The computational time of the distributed MPC is around 0.7s at each time step, which is sufficiently fast as a real-time control solution to wind farm operations

Feasibility studies of a converter-free grid-connected offshore hydrostatic wind turbine

Owing to the increasing penetration of renewable power generation, the modern power system faces great challenges in frequency regulations and reduced system inertia. Hence, renewable energy is expected to take over part of the frequency regulation responsibilities from the gas or hydro plants and contribute to the system inertia. In this article, we investigate the feasibility of frequency regulation by the offshore hydrostatic wind turbine (HWT). The simulation model is transformed from NREL (National Renewable Energy Laboratory) 5-MW gearbox-equipped wind turbine model within FAST (fatigue, aerodynamics, structures, and turbulence) code. With proposed coordinated control scheme and the hydrostatic transmission configuration of the HWT, the `continuously variable gearbox ratio' in turbulent wind conditions can be realised to maintain the constant generator speed, so that the HWT can be connected to the grid without power converters in-between. To test the performances of the control scheme, the HWT is connected to a 5-bus grid model and operates with different frequency events. The simulation results indicate that the proposed control scheme is a promising solution for offshore HWT to participated in frequency response in the modern power system