Wave Energy Control Systems: Robustness Issues

While traditional feedback control systems enjoy relatively good sensitivity properties, energy maximising wave energy converter (WEC) control systems have particular characteristics which challenge the application of traditional feedback and robust control methods. In particular, the relationship between plant and controller is largely defined by the need to maximise power transfer, and the controller contains a feedforward component which is difficult to robustify. Typically, WEC control systems are based on linear model descriptions, but this belies the true nonlinearity of WEC hydrodynamics (particularly under controlled conditions) and the associated power take-off (PTO) system. This paper examines two popular WEC control structures and examines the sensitivity of these structures to parameter variations, both in terms of closed-loop transfer functions and power absorbed. Some recommendations are also given on which WEC parameters need to be modelled with high accuracy

The impact of model predictive control structures and constraints on a wave energy converter with hydraulic power take off system

Ocean waves present a promising renewable energy source, but are challenging to harness given their irregular nature. In order to maximize energy capture on wave energy converters (WECs), power take off (PTO) systems are typically used to effectively adjust the device’s resonant frequency. Optimal control techniques can oversee the PTO operation to maximize overall power output, but optimization in real-time poses difficulties given the wave variability and underlying constraints of the system. This study compares two different model predictive control approaches. One method uses only a model of the hydrodynamics of the WEC while the second has a state space model that includes the WEC hydrodynamics as the dynamics of a hydraulic PTO system. The impact of the PTO constraints, control structure and control prediction horizon on the wave energy converter control performance was explored and quantified for irregular wave conditions. Results show that utilizing a model that includes both the hydrodynamics and PTO dynamics can increase power output by 23% compared to an approach that uses the hydrodynamics only

Validating a Wave-to-Wire Model for a Wave Energy Converter—Part II: The Electrical System

The incorporation of the full dynamics of the different conversion stages of wave energy converters (WECs), from ocean waves to the electricity grid, is essential for a realistic evaluation of the power flow in the drive train. WECs with different power take-off (PTO) systems, including diverse transmission mechanisms, have been developed in recent decades. However, all the different PTO systems for electricity-producing WECs, regardless of any intermediate transmission mechanism, include an electric generator, linear or rotational. Therefore, accurately modelling the dynamics of electric generators is crucial for all wave-to-wire (W2W) models. This paper presents the models for three popular rotational electric generators (squirrel cage induction machine, permanent magnet synchronous generator and doubly-fed induction generator) and a back-to-back (B2B) power converter and validates such models against experimental data generated using three real electric machines. The input signals for the validation of the mathematical models are designed so that the whole operation range of the electrical generators is covered, including input signals generated using the W2W model that mimic the behaviour of different hydraulic PTO systems. Results demonstrate the effectiveness of the models in accurately reproducing the characteristics of the three electrical machines, including power losses in the different machines and the B2B converter.This material is based on works supported by the Science Foundation Ireland under Grant No. 13/IA/1886

Wave energy control: status and perspectives 2020

Wave energy has a significant part to play in providing a carbon-free solution to the world’s increasing appetite for energy. In many countries, there is sufficient wave energy to cater for the entire national demand, and wave energy also has some attractive features in being relatively uncorrelated with wind, solar and tidal energy, easing the renewable energy dispatch problem. However, wave energy has not yet reached commercial viability, despite the first device designs being proposed in 1898. Control technology can play a major part in the drive for economic viability of wave energy and this paper charts the progress made since the first wave energy control systems were suggested in the 1970s, and examines current outstanding challenges for the control community

Receding Horizon Pseudospectral Control for Energy Maximization With Application to Wave Energy Devices

This paper addresses the issue of real-time control for applications, subject to physical constraints, involving an energy maximization objective. Typical application areas include renewable energy systems where, in spite of the fact that the raw energy resource is free, the capital and operational costs associated with the energy conversion process are not. In addition, economic energy delivery can only be achieved if the conversion device is operated efficiently. Previous approaches to this problem include model predictive control (MPC), but the computational cost associated with MPC can be high. Pseudospectral solutions show considerable promise in achieving a good balance between performance and computation, but currently available solutions deal with fixed-period optimization. In this paper, a receding horizon real-time pseudospectral control is developed, based on half-range Chebyshev Fourier basis functions, which can accurately represent harmonic signals in the application domain, while also efficiently dealing with the signal truncation effects associated with a receding horizon formulation. An application example, based on a wave energy converter, is used to illustrate the new control algorithm

Application of Nonlinear Model Predictive Controller for Ocean Wave Energy Conversion Systems

This work addresses the application of Nonlinear Model Predictive Control (NMPC) to a class of ocean wave energy conversion systems in which the cost functional is not in a standard quadratic form, and the WEC model includes the nonlinear effects, such as the hydrodynamic viscous drag. The NMPC implementation is extended for MIMO WEC problems. Hybrid testing of the proposed method is performed using Linear Testbed (LTB) wave simulator at Wallace Energy Systems and Renewables Facility (WESRF) at Oregon State University. Simulations and experiments are conducted to verify the proposed methodology