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Developing wave energy converter technology requires physical-scale model experiments. To use and compare such experimental data reliably, its quality must be quantified through an uncertainty analysis. To avoid uncertainty analysis problems for wave energy converter models, such as providing partial derivatives for time-varying quantities within n...
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... is repeated M times to obtain a distribution for the possible DRE result values. From this distribution, mean í µí± MCM and standard deviation sMCM statistics can be calculated (sMCM is the combined standard uncertainty uc of the DRE). The selection of M depends on when the standard deviation has converged (M = 1000 was used in this study, see Fig. 3 for convergence study used to determine M). Typically, convergence of 1-5% is reached after relatively few iterations (< 500). Once a converged value of uc is obtained, the expanded uncertainty for the result at a 95% confidence level is U = 2 uc. B. Mathematical model 1) Hydrodynamic power: In line with previous experiments of a ...
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... determine how many iterations of the MCM simulation are necessary, a convergence study must be conducted (fig. 3). Convergence is determined by calculating at each iteration the combined standard deviation sMCM of a DRE of interest, for example OWC power Ph. Subsequently plotting sMCM shows the convergence behaviour. From fig. 3 it may be seen that after only 300 iterations the value has converged to within 2% of the fully converged value. We ...
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... determine how many iterations of the MCM simulation are necessary, a convergence study must be conducted (fig. 3). Convergence is determined by calculating at each iteration the combined standard deviation sMCM of a DRE of interest, for example OWC power Ph. Subsequently plotting sMCM shows the convergence behaviour. From fig. 3 it may be seen that after only 300 iterations the value has converged to within 2% of the fully converged value. We repeated this process for all primary DRE's, and deemed that after 100 iterations the values were fully ...
Citations
... To date, within the realm of wave energy conversion, the literature on robust optimization has predominantly focused on the development of robust control frameworks [10][11][12][13][14][15][16][17]. Furthermore, concerning the study of wave energy and WEC uncertainties, the existing literature primarily covers environmental [18][19][20][21][22] and full/high-scale prototyping or experimental uncertainties and subsystems' influence on performance [23][24][25][26][27][28][29]. The neighboring Reliability-Based Design Optimization (RBDO) field of research directs its attention to WEC structural and maintenance cost uncertainties [30] (in which the so-called Wavestar device is considered as a case study) and the power take-off (PTO) reliability relationship with hull geometry [31]. ...
Among the challenges generated by the global climate crisis, a significant concern is the constant increase in energy demand. This leads to the need to ensure that any novel energy systems are not only renewable but also reliable in their performance. A viable solution to increase the available renewable energy mix involves tapping into the potential available in ocean waves and harvesting it via so-called wave energy converters (WECs). In this context, a relevant engineering problem relates to finding WEC design solutions that are not only optimal in terms of energy extraction but also exhibit robust behavior in spite of the harsh marine environment. Indeed, the vast majority of design optimization studies available in the state-of-the-art consider only perfect knowledge of nominal (idealized) conditions, neglecting the impact of uncertainties. This study aims to investigate the information that different robustness metrics can provide to designers regarding optimal WEC design solutions under uncertainty. The applied methodology is based on stochastic uncertainty propagation via a Monte Carlo simulation, exploiting a meta-model to reduce the computational burden. The analysis is conducted over a dataset obtained with a genetic algorithm-based optimization process for nominal WEC design. The results reveal a significant deviation in terms of robustness between the nominal Pareto set and those generated by setting different thresholds for robustness metrics, as well as between devices belonging to the same nominal Pareto frontier. This study elucidates the intrinsic need for incorporating robust optimization processes in WEC design.
... In the cases above mentioned is common to approach the uncertainty propagation problem with a classical partial derivative method. Instead, in [10], a Monte Carlo method is explored as a pratical alternative for complex models. For what concern WECs array, the models physical validation presents some difficulities due to replicating numerical model characteristics complications. ...
The optimisation design of Wave Energy Converters (WEC) to reduce the cost of energy of the technology is a widely investigated topic. In literature classical optimisation strategies have been presented and applied to identify the optimal system parameters of WECs to optimise specific techno-economic metrics. The performance of the optimal identified devices relies on these nominal parameters and it can be strongly affected by construction and modelling uncertainties. In this context, the concept of robustness of the optimal solution plays a relevant role in the identification of a device whose performance is affected as little as possible by uncertainties of various kinds. In the first part of this paper different declinations of robustness concept are derived from other fields of application and described. The identified robustness indexes are then applied to optimal solutions obtained via classical optimisation to evaluate its importance in the design process of WECs. Strictly related to this kind of methodology is the Sensitivity Analysis (SA) technique, it aims to investigate how the input variation (due to uncertainties or external noise or additional environmental parameters) influences the output results of a defined numerical model and highlight the relative input parameters relevance. Sensitivity Analysis, therefore, can be a valuable tool applicable in the uncertainty set estimation to identify the variables most subject to such uncertainties and their prominence. The main objective of the work is to underline the importance of introduce the robustness evaluation of WECs during the optimisation process since classical optimisation techniques can lead to solutions that are affected by uncertainties.
... For example, spatial variations of generated waves in wave tanks [19] coupled with difficult to measure interactions and absorbed power of an array of heaving-buoy WECs lead to uncertainty levels that mostly concealed motions and power [20]. Capture width ratio of oscillating water column (OWC) WECs has also been shown to be especially susceptible to uncertainty [21,22]. More broadly, uncertainty extends beyond the laboratory to uncertainty in wave resource assessment [23e25], mean annual energy production (MAEP) estimates [25,26], and open water tests [27]. ...
... [28]. While these are a good step toward rigorous, standardised best practices, the guidance is relatively immature; it lacks important uses of UA, such pre-test or general uncertainty analysis, alternative methods to propagate uncertainty such as the Monte Carlo method (MCM) [22,29,30], and WEC-specific methods for evaluating Type A and Type B uncertainty [21]. To refine this guidance, we carried out a 1:30 scale experiment of a case study oscillating water column (OWC) WEC, based on Australian company Wave Swell Energy's Uniwave® technology, 1 which is a bottom-fixed device with a unidirectional flow power take-off (PTO) system enabled by passive valves. ...
... The output of the MCM is the standard deviation of the PDF of Y, taken as the general uncertainty u G ðYÞ. An appropriate value for M is determined by calculating the standard deviation of Y at each iteration and stopping the process when a converged value is reached ( [22]). A converged value to within 5% is considered to give an acceptable approximation of u G ðYÞ (Mz 5000 is typically sufficient). ...
Ocean wave energy has significant technical potential but limited full-scale deployments and technology convergence. Consequently, guidelines for developing wave energy converters (WECs) are still developing themselves, especially around experimental uncertainty analysis (UA). To develop a comprehensive WEC-specific UA methodology, we conducted a 1:30 scale experiment of a case study oscillating water column (OWC) WEC. This paper presents the methodology, which describes UA principles and means to identify parameters causing uncertainty, and demonstrates new WEC-specific UA methods: general uncertainty analysis (GUA), the Monte Carlo method (MCM) for uncertainty propagation, and Type A and Type B uncertainty evaluation. Results show the expanded uncertainty averaged ± 16% for capture width ratio and ± 6% for wave loads; Type B uncertainty tended to be slightly larger than Type A uncertainty; and uncertainty in regular waves slightly larger than irregular waves. The MCM was found to be effective and efficient in uncertainty propagation. In general, given WECs tend to maximise motions, use a power take-off system, and must survive storms, WEC model tests may be especially susceptible to uncertainty due to nonlinearities and modelling complexities. In conclusion, UA should be carried out in WEC model test experiments. We close with recommendations for refining relevant international guidelines.
... This considers the total mean As with previous experimental investigations conducted using bent duct type OWC de-173 vices (cf. [6,[44][45][46][47]49]), two assumptions were made regarding the volume flux. Firstly, it 174 is understood that the dynamic oscillation within the OWC chamber will induce different 175 excitation modes of the free surface. ...
... which was the lowest of the tested damping. Orphin et al. [49] found that as damping 884 increased, the uncertainty associated with δ consequently decreased as the relationship be-885 tween p c and Q became more linear. As such, it is assumed that the uncertainty associated 886 with the optimal damping condition, LDV 5, will be substantially less than that presented 887 for the LDV 1 condition investigated. ...
Currently, ocean wave energy technology is in its infancy relative to the mature renewable
energy technologies such as wind and solar. Due to its early stage of development, ocean
wave energy has high associated Levelised Cost of Electricity (LCOE), a measure of lifetime costs relative to lifetime energy production. Several solutions have been derived in an attempt to reduce this high LCOE, of which breakwater integration of wave energy converters presents a viable option. Current full-scale commercial and demonstration devices indicate that OWC device integrated breakwaters are typically limited to nearshore and onshore operational regions. However, industries such as aquaculture and offshore wind are exploring the viability of placing these structures in deeper waters, where these traditional concepts would not be applicable, providing opportunity for the development of floating offshore multi-purpose structures. This article describes a proof-of-concept for a floating breakwater integrated with Oscillating Water Column (OWC) Wave Energy Converters (WEC). For an integrated device of this type there are multiple key aspects that are inter-related and each must be understood: energy extraction performance, wave attenuation and quantifying platform motions. In order to adequately report on each aspect in a logical manner the study is presented in two parts. This paper covers the energy extraction aspects, while the second part deals with wave attenuation and motion characteristics [1]. The wave energy extraction characteristics of the installed devices are explored across parameters including device configurations, breakwater width, power take-off damping, wave height and motion constraints, all of which was achieved through model scale hydrodynamic experimentation.
The major findings indicate that OWC device spacing is a key parameter in the design of
multi-device structures, as device-device interaction can have constructive or destructive
interferences on the energy extraction. Additionally, the results of the OWC device performance, under the influence of the aforementioned parameters, provides new insights to the development of floating offshore multi-purpose structures and their feasibility.
Guidelines aimed at assisting offshore renewable energy technology developers in getting the most of testing campaigns. This document covers laboratory and field testing.
This research presents a methodology for carrying out uncertainty analysis on measurements made during wave basin testing of an oscillating water column wave energy converter. Values are determined for Type A and Type B uncertainty for each parameter of interest, and uncertainty is propagated using the Monte Carlo method to obtain an overall Expanded Uncertainty with a 95% confidence level associated with the Capture Width Ratio of the device. An analysis into the impact of reflections on the experimental results reveals the importance of identifying the incident and combined wave field at each measurement location used to determine device performance, in order to avoid misleading results.
Maritime structure integration is widely considered as a potential solution for reducing the high Levelised Cost of Electricity (LCOE) associated with Wave Energy Converter (WEC) technologies. However, the majority of published research has focused on fixed structure integration [1,2], with far fewer investigating the potential for floating structure integration [3]. Expanding on previous works [4,5], this article investigates the performance of a π-type floating breakwater integrated with multiple Oscillating Water Column (OWC) WECs through model scale hydrodynamic experimentation. While under varying structural arrangements including device configurations and motion constraints, the model was subjected to 13 generic irregular wave spectra. Results of the experimental investigation illustrate that OWC device integration provides distinct benefits to the non-dimensional performance parameters of the floating breakwater in irregular sea states, which correlates strongly with the results obtained from previous regular wave analyses [4,5]. With firm correlation between the regular and irregular analyses, it is hypothesized that device development could potentially forgo regular wave investigations in preference of irregular wave testing, as it yields a broader bandwidth of results with reduced temporal requirements. Similarly, it is illustrated that the irregular non-dimensional parameter spectra can be used to effectively predict the performance characteristics of the device across different sea states. This article furthers the concept validation and feasibility of OWC WEC integrated floating breakwaters, and aids in the progression of the concept through the Technology Readiness Levels.
