David Forehand

A Review of Numerical Modelling of Wave Energy Converter Arrays

Large-scale commercial exploitation of wave energy is certain to require the deployment of wave energy converters (WECs) in arrays, creating ‘WEC farms’. An understanding of the hydrodynamic interactions in such arrays is essential for determining optimum layouts of WECs, as well as calculating the area of ocean that the farms will require. It is equally important to consider the potential impact of wave farms on the local and distal wave climates and coastal processes; a poor understanding of the resulting environmental impact may hamper progress, as it would make planning consents more difficult to obtain. It is therefore clear that an understanding the interactions between WECs within a farm is vital for the continued development of the wave energy industry.To support WEC farm design, a range of different numerical models have been developed, with both wave phase-resolving and wave phase-averaging models now available. Phase-resolving methods are primarily based on potential flow models and include semi-analytical techniques, boundary element methods and methods involving the mild-slope equations. Phase-averaging methods are all based around spectral wave models, with supra-grid and sub-grid wave farm models available as alternative implementations.The aims, underlying principles, strengths, weaknesses and obtained results of the main numerical methods currently used for modelling wave energy converter arrays are described in this paper, using a common framework. This allows a qualitative comparative analysis of the different methods to be performed at the end of the paper. This includes consideration of the conditions under which the models may be applied, the output of the models and the relationship between array size and computational effort. Guidance for developers is also presented on the most suitable numerical method to use for given aspects of WEC farm design. For instance, certain models are more suitable for studying near-field effects, whilst others are preferable for investigating far-field effects of the WEC farms. Furthermore, the analysis presented in this paper identifies areas in which the numerical modelling of WEC arrays is relatively weak and thus highlights those in which future developments are required.Copyright

In-tank tests of a dielectric elastomer generator for wave energy harvesting

Wave energy harvesting is one of the most promising applications for Dielectric Elastomer Generators. A simple and interesting concept of a Wave Energy Converter based on Dielectric Elastomers is the Polymeric Oscillating Water Column (Poly-OWC). In this paper, preliminary experimental results on the assessment of a small-scale Poly-OWC prototype are presented. The scale of the considered prototype is 1:50. Tests are conducted in a wave-flume by considering sea state conditions with different wave amplitudes and frequencies. The obtained experimental results confirm the viability of the Poly-OWC device.

A Fully Coupled Wave-to-Wire Model of an Array of Wave Energy Converters

This paper describes a fully coupled, wave-to-wire time-domain model that can simulate the hydrodynamic, mechanical, and electrical response of an array of wave energy converters. Arrays of any configuration can be simulated to explore both the effects of the array on the electricity network and of network events on the devices within the array. State-space modeling of the hydrodynamic radiation forces enables fast and accurate prediction of the interacting response of multiple devices, including the effects of wave climate, control strategies, and network power flow. Case studies include the demonstration of the bidirectional interaction of the array and the network.

Modelling arrays of wave energy converters connected to weak rural electricity networks

This paper describes a modelling framework developed in Matlab/Simulink that has been used to study, analyse and improve the network integration of Wave Energy Converters (WECs). It presents and discusses a generic, time domain, resource-to-wire model that can be used to explore the effects of: increased device numbers, array size and physical positioning; and the adjustment of control parameters. The three-dimensional wave field is modelled as non-stationary, with statistical characteristics that are extracted from measured wave elevation time series to simulate increasingly realistic sea conditions. Each heaving buoy has high-pressure oil power take off with on-board energy storage, driving Doubly Fed Induction Generators (DFIGs). The results obtained from simulations using this model are used to demonstrate the overall effects of storage on real power production, and the effects of imaginary power control on network voltage profile. The opportunities for improved network integration are identified and discussed.

Modeling of an Oscillating Wave Surge Converter With Dielectric Elastomer Power Take-Off

This paper introduces a novel concept of Oscillating Wave Surge Converter, named Poly-Surge, provided with a Dielectric Elastomer Generator (DEG) as Power Take-Off (PTO) system.DEGs are transducers that employ rubber-like polymers to conceive deformable membrane capacitors capable of directly converting mechanical energy into electricity. In particular, a Parallelogram Shaped DEG is considered.In the paper, a description of the Poly-Surge is outlined and engineering considerations about the operation and control of the device are presented. In addition, a mathematical model of the system is provided. Linear time-domain hydrodynamics is assumed for the primary interface, while a non linear electro-hyperelastic model is employed for the DEG PTO.A design approach for the Poly-Surge DEG PTO is introduced which aims at maximizing the energy produced in a year by the device in a reference wave climate, defined by a set of equivalent monochromatic wave conditions. A comparison is done with two other WEC models that employ the same primary interface but are equipped with mathematically linear PTO systems under optimal and suboptimal control. The results show promising performance of annual energy productivity, with slightly reduced values for the Poly-Surge, even if a very basic architecture and control strategy are assumed.© 2014 ASME

Control of a Point Absorber Using Reinforcement Learning

This work presents the application of reinforcement learning for the optimal resistive control of a point absorber. The model-free Q-learning algorithm is selected in order to maximise energy absorption in each sea state. Step changes are made to the controller damping, observing the associated penalty, for excessive motions, or reward, i.e. gain in associated power. Due to the general periodicity of gravity waves, the absorbed power is averaged over a time horizon lasting several wave periods. The performance of the algorithm is assessed through the numerical simulation of a point absorber subject to motions in heave in both regular and irregular waves. The algorithm is found to converge towards the optimal controller damping in each sea state. Additionally, the model-free approach ensures the algorithm can adapt to changes to the device hydrodynamics over time and is unbiased by modelling errors.

Control of a Realistic Wave Energy Converter Model Using Least-Squares Policy Iteration

An algorithm has been developed for the resistive control of a nonlinear model of a wave energy converter using least-squares policy iteration, which incorporates function approximation, with tabular and radial basis functions being used as features. With this method, the controller learns the optimal power take-off damping coefficient in each sea state for the maximization of the mean generated power. The performance of the algorithm is assessed against two online reinforcement learning schemes: Q-learning and SARSA. In both regular and irregular waves, least-squares policy iteration outperforms the other strategies, especially when starting from unfavorable conditions for learning. Similar performance is observed for both basis functions, with a smaller number of radial basis functions underfitting the Q-function. The shorter learning time is fundamental for a practical application on a real wave energy converter. Furthermore, this paper shows that least-squares policy iteration is able to maximize the energy absorption of a wave energy converter despite strongly nonlinear effects due to its model-free nature, which removes the influence of modeling errors. Additionally, the floater geometry has been changed during a simulation to show that reinforcement learning control is able to adapt to variations in the system dynamics.

On the performance of an array of floating wave energy converters for different water depths

A frequency domain hydrodynamic assessment was carried out using WAMIT on buoy type wave energy converters (WECs), constrained to move in heave only. Control of the power take-off (PTO) system has been established through real control (damping resistance only) for an isolated WEC. This fixed value has then been applied to all WECs in an array of ten devices, set out in two rows. The array has been tested in six water depths, represented by the relative water depth d/λ0, ranging from 0.25 to infinite depth, where λ0 is the resonant wavelength of an isolated WEC in infinitely deep water. Incremental reductions in water depth, result in an drop in peak q-factor, which was also marked with a small shift in ka. It was deemed appropriate here to re-tune the PTO settings for the different water depths.The various interactions within the array were examined in more detail by considering the radiation forces between WECs. Results are presented, highlighting the most significant device interactions due to the variations in water depth. The growth and shift in ka of the peak forces are also evident in shallower water. Depth modified JONSWAP and Pierson-Moskowitz spectra have also been applied in order to calculate mean power production estimates for the various water depths.For the particular array and conditions considered, there was a clear downward trend in power captured when moving into progressively shallower water. This was in part due to the reduction in total energy available in the shallower spectra, but also because the frequency of peak performance of the array has shifted significantly.Copyright