Matthew Folley

Nearshore oscillating wave surge converters and the development of Oyster

Oscillating wave surge converters (OWSCs) are a class of wave power technology that exploits the enhanced horizontal fluid particle movement of waves in the nearshore coastal zone with water depths of 10–20 m. OWSCs predominantly oscillate horizontally in surge as opposed to the majority of wave devices, which oscillate vertically in heave and usually are deployed in deeper water. The characteristics of the nearshore wave resource are described along with the hydrodynamics of OWSCs. The variables in the OWSC design space are discussed together with a presentation of some of their effects on capture width, frequency bandwidth response and power take-off characteristics. There are notable differences between the different OWSCs under development worldwide, and these are highlighted. The final section of the paper describes Aquamarine Powers 315 kW Oyster 1 prototype, which was deployed at the European Marine Energy Centre in August 2009. Its place in the OWSC design space is described along with the practical experience gained. This has led to the design of Oyster 2, which was deployed in August 2011. It is concluded that nearshore OWSCs are serious contenders in the mix of wave power technologies. The nearshore wave climate has a narrower directional spread than the offshore, the largest waves are filtered out and the exploitable resource is typically only 10–20% less in 10 m depth compared with 50 m depth. Regarding the devices, a key conclusion is that OWSCs such as Oyster primarily respond in the working frequency range to the horizontal fluid acceleration; Oyster is not a drag device responding to horizontal fluid velocity. The hydrodynamics of Oyster is dominated by inertia with added inertia being a very significant contributor. It is unlikely that individual flap modules will exceed 1 MW in installed capacity owing to wave resource, hydrodynamic and economic constraints. Generating stations will be made up of line arrays of flaps with communal secondary power conversion every 5–10 units.

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

The effect of the spectral distribution of wave energy on the performance of a bottom hinged flap type wave energy converter

The power output from a wave energy converter is typically predicted using experimental and/or numerical modelling techniques. In order to yield meaningful results the relevant characteristics of the device, together with those of the wave climate must be modelled with sufficient accuracy.The wave climate is commonly described using a scatter table of sea states defined according to parameters related to wave height and period. These sea states are traditionally modelled with the spectral distribution of energy defined according to some empirical formulation. Since the response of most wave energy converters vary at different frequencies of excitation, their performance in a particular sea state may be expected to depend on the choice of spectral shape employed rather than simply the spectral parameters. Estimates of energy production may therefore be affected if the spectral distribution of wave energy at the deployment site is not well modelled. Furthermore, validation of the model may be affected by differences between the observed full scale spectral energy distribution and the spectrum used to model it.This paper investigates the sensitivity of the performance of a bottom hinged flap type wave energy converter to the spectral energy distribution of the incident waves. This is investigated experimentally using a 1:20 scale model of Aquamarine Power’s Oyster wave energy converter, a bottom hinged flap type device situated at the European Marine Energy Centre (EMEC) in approximately 13m water depth. The performance of the model is tested in sea states defined according to the same wave height and period parameters but adhering to different spectral energy distributions.The results of these tests show that power capture is reduced with increasing spectral bandwidth. This result is explored with consideration of the spectral response of the device in irregular wave conditions. The implications of this result are discussed in the context of validation of the model against particular prototype data sets and estimation of annual energy production.Copyright

The control of wave energy converters using active bipolar damping

A novel method for controlling wave energy converters using active bipolar damping is described and compared with current control methods. The performance of active bipolar damping is modelled numerically for two distinct types of wave energy converter and it is found that in both cases the power capture can be significantly increased relative to optimal linear damping. It is shown that this is because active bipolar damping has the potential for providing a quasi-spring or quasi-inertia, which improves the wave energy converters tuning and amplitude of motion, resulting in the increase in power capture observed. The practical implementation of active bipolar damping is also discussed. It is noted that active bipolar damping does not require a reactive energy store and thereby reduces the cost and eliminates losses due to the cycling of reactive energy. It is also noted that active bipolar damping could be implemented using a single constant pressure double-acting hydraulic cylinder and so potentially represents a simple, efficient, robust and economic solution to the control of wave energy converters.

Numerical Simulation of Wave Power Devices Using a Two Fluid Free Surface Solver

A generic two-fluid (water/air) numerical model has been developed and applied for the simulation of the complex fluid flow around a wave driven rotating vane near a shoreline in the context of a novel wave energy device OWSC (Oscillating wave surge converter). The underlying scheme is based on the solution of the incompressible Euler equations for a variable density fluid system for automatically capturing the interface between water and air and the Cartesian cut cell method for tracking moving solid boundaries on a background stationary Cartesian grid. The results from the present study indicate that the method is an effective tool for modeling a wide range of free surface flow problems.

Preliminary cross-validation of wave energy converter array interactions

The development of wave energy for utility-scale electricity production requires an understanding of how wave energy converters will interact with each other when part of a wave farm. Without this understanding it is difficult to calculate the energy yield from a wave farm and consequently the optimal wave farm layout and configuration cannot be determined. In addition, the uncertainty in a wave farm’s energy yield will increase the cost of finance for the project, which ultimately increases the cost of energy.Numerical modelling of wave energy converter arrays, based on potential flow, has provided some initial indications of the strength of array interactions and optimal array configurations; however, there has been limited validation of these numerical models. Moreover, the cross-validation that has been completed has been for relatively small arrays of wave energy converters. To provide some validation for large array interactions wave basin testing of three different configurations of up to 24 wave energy converters has been completed. All tests used polychromatic (irregular) sea-states, with a range of long-crested and short-crested seas, to provide validation in realistic conditions.The physical model array interactions are compared to those predicted by a numerical model and the suitability of the numerical and physical models analysed. The results are analysed at three different levels and all provide support for the cross-validation of the two models. The differences between the physical and numerical model are also identified and the implications for improving the modelling discussed.Copyright

The Wave Energy Resource

Understanding the hydrodynamics of waves and the wave energy resource is fundamental to the good design of wave energy converters. The wave energy resource can be defined by its temporal, directional and spectral characteristics, although many representations of the wave energy resource result in the removal of this information, with a consequential distortion of the apparent resource. This chapter discusses how wave energy resource data may be generated using numerical model and validated using site measurements. The chapter also discusses the processes that afffect wave propagation and lead to wave transformation. In its totality, the chapter provides sufficient details of the wave resource to allow an assessment of any particular wave resource assessment to be made, together wtith its potential impact on the performance of a wave energy converter.

Determining Mean Annual Energy Production

Abstract The calculation of the mean annual energy production (MAEP) is critical to the assessment of the levelized cost of energy for a wave energy converter or wave farm. Fundamentally, the MAEP is equal to the sum of the product of the power capture of a set of sea-states and their average annual occurrence. In general, it is necessary in the calculation of the MAEP to achieve a balance between computational demand and accuracy. A high accuracy can be obtained using a large number of sea-states with a high fidelity power capture model; however, this is likely to result in a high computational demand. Typically, the models most suitable for calculating the MAEP are time-domain models, spectral-domain models, and models obtained through system identification. The traditional method for representing the wave climate is using a scatter table, indexed by significant wave height and energy period; however, it has been found that this can lead to high errors in the MAEP due to the necessary assumptions regarding spectral shape. Alternative representations include an extensive time series of all the sea-states or an abridged set, where the set is chosen to cover the range of sea-states as completely as possible using techniques such as the k-means algorithm or the maximum distance algorithm. Once the wave climate is defined the power capture for each representative sea-state in the wave climate can be determined using a power matrix, indexed by significant wave height and energy period, modelling all the sea-states or modelling a representative set of sea-states defined using the radial basis functions method. The use of the power matrix is most popular, but also least accurate, whilst modelling all the sea-states is the most computationally demanding, but also the most accurate.