• Energy Research

AbstractFar wake velocities of a single horizontal axis three-bladed turbine in shallow flow have been measured previously in the laboratory and shown to have self-similar velocity deficit profiles. Wake velocities of arrays of turbines with one, two and three transverse rows have also been measured and simply superimposing the velocity deficits for a single turbine is shown to give accurate prediction of combined wake width and velocity deficit, accounting for variable downstream blockage through volume flux conservation. Array efficiency is defined as the ratio of total power generated to what would be generated by the same turbines in isolation. From prescribed initial turbine positions, generally determined intuitively or by practical considerations, adjusting the turbine positions to increase the power from each turbine, using the chain rule, shows that relatively small movements of 3–4 rotor diameters may increase array efficiency to over 90%.

Wave power capture applied on a squid jigging ship is assessed in this paper; this would decrease the operating cost of ships and reduce carbon emissions. Firstly, the history of wave energy devices and wave energy generation on ships are briefly reviewed. Then, a new wave energy device on an ocean squid jigging ship is designed. The linear mathematical system model of the device, and WAMIT software are used to calculate wave energy captured. The floating bodies of the device is designed to take advantage of resonance. By comparing wave capture width ratio of the float with arm hinged on the ship, it is found that wave capture width ratio of the device is highest when the arm length is half a wavelength. The numerical method is validated by experimental tests which are presented in details from setup, data treatment to wave energy capture ratio calculated. Based on a resonance criterion, 20 wave energy device layouts of the ocean squid jigging ship are designed. From numerical simulation the optimum radius of the floating body is 2 m, and the maximum annual average power among these devices is 136 kW at Northwest Pacific fishery ground, which can provide about 10 % of the power consumption for the ocean squid jigging ship.

Ocean waves provide a promising and abundant renewable energy resource. One reason wave energy technology is still not mature enough for commercialization is the high unit cost of generated electricity. This needs to be improved by a combination of device and associated controller design. A multi-float and multi-mode-motion wave energy converter (M-WEC) enables much higher energy conversion compared with a single-float, single-mode WEC (S-WEC); however, the added complexity in dynamics of a M-WEC makes the corresponding controller design more challenging. While the majority of current WEC control research has been based on the control of S-WECs it has shown that control can significantly improve energy conversion. This paper aims to design a linear non-causal optimal controller for a M-WEC to demonstrate that this improvement also applies to more complex WEC systems. We choose a multi-body attenuator type M-WEC called M4 as a case study for which the desirable feature of predominantly linear dynamics has been demonstrated. This means that a linear controller can be designed based on a linear hydrodynamic model without introducing an intractable computational burden for real-time controller implementation. Numerical results show that the linear non-causal optimal controller can significantly improve the power capture of M4 over a broad range of peak spectral wave periods by $\text{40}{\%}$ to $\text{100}{\%}$ .

As a non-causal optimal control problem, the performance of wave energy converter (WEC) control relies on the accuracy of the future incoming wave prediction. However, the inevitable prediction errors can degrade WEC performance dramatically especially when a long prediction horizon is needed by a WEC non-causal optimal controller. This paper proposes a novel non-causal linear optimal control with adaptive sliding mode observer (NLOC+ASMO) scheme, which can effectively mitigate the control performance degradation caused by wave prediction errors. This advantage is achieved by embedding the following enabling techniques into the scheme: (i) an adaptive sliding mode observer (ASMO) to estimate current excitation force in real-time with explicitly formulated boundary of estimation error, (ii) an auto-regressive (AR) model to predict the incoming excitation force with explicitly formulated boundary of prediction error using a set of latest historical data of ASMO estimations from (i), and (iii) a compensator to compensate for both the estimation error and the prediction error of excitation force. Moreover, the proposed NLOC+ASMO scheme does not cause heavy computational load enabling its real-time implementation on standard computational hardware, which is especially critical for the control of WECs with complicated dynamics. The proposed NLOC+ASMO framework is generic and can be applied to a wide range of WECs, and in this paper we demonstrate the efficacy by using a multi-float and multi-motion WEC called M4 as a case study, whose control problem is more challenging than the widely studied point absorbers. Simulation results show the effectiveness of the proposed control scheme in a wide range of sea states, and it is also found that the controller is not sensitive to change of ASMO parameters.

Tidal stream turbines operate in the harsh marine environment, subjected to turbulence, wave action and wakes from upstream devices when deployed in arrays. Turbines may be mounted on the sea bed or on floating platforms. Numerical models are invaluable to study individual and array performance and their interaction with environmental flows. To date, shallow water models and three-dimensional Reynolds Averaged Navier-Stokes (RANS) simulations predominate the simulation of turbine arrays, while Large-Eddy Simulation (LES) is becoming more widely used due to availability of high-performance computing resources. The accuracy of turbine performance and load prediction depends on the ability to represent turbulence in the tidal flow and unsteady wake effects. Inclusion of waves increases the modelling complexity and is particularly significant for floating platforms. In this Vision Paper, we provide a perspective on the numerical approaches currently used for modelling tidal flows and marine turbines, suggesting future challenges envisaged in this field.

Wave energy converters with capacity similar to, or greater than, wind turbines are desirable for the supply of electricity to the grid. It is shown that this may be provided by multiple floats in a hinged raft-type configuration with multi-mode forcing. The case analysed has 8 floats and 4 power take off (PTO) units. Analysis is based on linear diffraction-radiation modelling, validated in wave basin experiments with a smaller number of floats. Control is desirable to improve energy capture, mainly demonstrated for point absorbers, but this has not previously been applied to such a complex problem with many degrees of freedom. The linear hydrodynamic model in a state-space form makes it possible to implement advanced control algorithms in real time. Linear non-causal optimal control (LNOC) is applied with wave force prediction from auto-regression. For the design case with zero heading, as the configuration heads naturally into the wave direction, energy capture is improved by between 21% and 83%. The energy capture is about 62% the maximum possible from idealised analyses. Off-design, non-zero headings are also analysed to indicate how energy capture can be reduced; the contribution from different modes of forcing varies with heading and energy capture is always improved by control, by several times at $90^{\circ }$ heading.

Recently, multi-float and multi-mode-motion wave energy converters (M-WECs) have been developed to improve energy conversion capability. Although model predictive control (MPC) can be very effective to solve the constrained energy maximization control problem of point absorber WECs, the increased complexity of the M-WEC hydrodynamics can bring significant challenges due to computational demand. This brief proposes a novel computational-efficient fast MPC (FMPC) design method for the M-WECs requiring complex linear hydrodynamic models. The controller design objective is to maximize the energy conversion with some available wave forecasting information and to satisfy state and control input constraints to ensure safe operation. The main advantage of the proposed FMPC is the reduced computational burden with a negligible impact on performance. A demonstrative numerical simulation based on a 1:50 laboratory-scale M-WEC design, M4, for which linear hydrodynamics has been verified experimentally, is presented to verify the efficacy of the proposed control method in terms of both computational load and energy output.

AbstractWave energy converters absorb wave power by mechanical damping for conversion into electricity and multi-float systems may have high capture widths. The kinetic energy of the floats causes waves to be radiated, generating radiation damping. The total wave power absorbed is thus due to mechanical and radiation damping. A floating offshore wind turbine platform also responds dynamically and damping plates are generally employed on semi-submersible configurations to reduce motion, generating substantial drag which absorbs additional wave power. Total wave power absorption is analysed here by linear wave diffraction–radiation–drag models for a multi-float wave energy converter and an idealised wind turbine platform, with response and mechanical power in the wave energy case compared with wave basin experiments, including some directional spread wave cases, and accelerations compared in the wind platform case. The total power absorption defined by capture width is input into a far field array model with directional wave spreading. Wave power transmission due a typical wind turbine array is only reduced slightly (less than 5% for a 10 × 10 platform array) but may be reduced significantly by rows of wave energy converters (by up to about 50%).