Assessment of primary energy conversions of oscillating water columns. I. Hydrodynamic analysis

This is an investigation on the development of a numerical assessment method for the hydrodynamic performance of an oscillating water column (OWC) wave energy converter. In the research work, a systematic study has been carried out on how the hydrodynamic problem can be solved and represented reliably, focusing on the phenomena of the interactions of the wave-structure and the wave-internal water surface. These phenomena are extensively examined numerically to show how the hydrodynamic parameters can be reliably obtained and used for the OWC performance assessment. In studying the dynamic system, a two-body system is used for the OWC wave energy converter. The first body is the device itself, and the second body is an imaginary “piston,” which replaces part of the water at the internal water surface in the water column. One advantage of the two-body system for an OWC wave energy converter is its physical representations, and therefore, the relevant mathematical expressions and the numerical simulation can be straightforward. That is, the main hydrodynamic parameters can be assessed using the boundary element method of the potential flow in frequency domain, and the relevant parameters are transformed directly from frequency domain to time domain for the two-body system. However, as it is shown in the research, an appropriate representation of the “imaginary” piston is very important, especially when the relevant parameters have to be transformed from frequency-domain to time domain for a further analysis. The examples given in the research have shown that the correct parameters transformed from frequency domain to time domain can be a vital factor for a successful numerical simulation.

Wave energy conversion of oscillating water column devices including air compressibility

This paper presents an investigation on air compressibility in the air chamber and its effects on the power conversion of oscillating water column (OWC) devices. As it is well known that for practical OWC plants, their air chambers may be large enough for accommodating significant air compressibility, the “spring effect,” an effect that is frequently and simply regarded to store and release energy during the reciprocating process of a wave cycle. Its insight effects on the device’s performance and power conversion, however, have not been studied in detail. This research will investigate the phenomena with a special focus on the effects of air compressibility on wave energy conversion. Air compressibility itself is a complicated nonlinear process in nature, but it can be linearised for numerical simulations under certain assumptions for frequency domain analysis. In this research work, air compressibility in the OWC devices is first linearised and further coupled with the hydrodynamics of the OWC. It is able to show mathematically that in frequency-domain, air compressibility can increase the spring coefficients of both the water body motion and the device motion (if it is a floating device), and enhance the coupling effects between the water body and the structure. Corresponding to these changes, the OWC performance, the capture power, and the optimised Power Take-off (PTO) damping coefficient in the wave energy conversion can be all modified due to air compressibility. To validate the frequency-domain results and understand the problems better, the more accurate time-domain simulations with fewer assumptions have been used for comparison. It is shown that air compressibility may significantly change the dynamic responses and the capacity of converting wave energy of the OWC devices if the air chamber is very large.

Floating wave energy converters: wave measurement & analysis techniques

The wave energy industry is entering a new phase of pre-commercial and commercial deployments of full-scale devices, so better understanding of seaway variability is critical to the successful operation of devices. The response of Wave Energy Converters to incident waves govern their operational performance and for many devices, this is highly dependent on spectral shape due to their resonant properties. Various methods of wave measurement are presented, along with analysis techniques and empirical models. Resource assessments, device performance predictions and monitoring of operational devices will often be based on summary statistics and assume a standard spectral shape such as Pierson-Moskowitz or JONSWAP. Furthermore, these are typically derived from the closest available wave data, frequently separated from the site on scales in the order of 1km. Therefore, variability of seaways from standard spectral shapes and spatial inconsistency between the measurement point and the device site will cause inaccuracies in the performance assessment. This thesis categorises time and frequency domain analysis techniques that can be used to identify changes in a sea state from record to record. Device specific issues such as dimensional scaling of sea states and power output are discussed along with potential differences that arise in estimated and actual output power of a WEC due to spectral shape variation. This is investigated using measured data from various phases of device development.

Cavity ring‑up spectroscopy for dissipative and dispersive sensing in a whispering gallery mode resonator

In whispering gallery mode resonator sensing applications, the conventional way to detect a change in the parameter to be measured is by observing the steady-state transmission spectrum through the coupling waveguide. Alternatively, sensing based on cavity ring-up spectroscopy, i.e. CRUS, can be achieved transiently. In this work, we investigate CRUS using coupled mode equations and find analytical solutions with a large spectral broadening approximation of the input pulse. The relationships between the frequency detuning, coupling gap and ring-up peak height are determined and experimentally verified using an ultrahigh Q-factor silica microsphere. This work shows that distinctive dispersive and dissipative transient sensing can be realised by simply measuring the peak height of the CRUS signal, which may improve the data collection rate.