Quantification of uncertainty in linear wave energy hydrodynamic models from experimental data

Mahdiyeh Farajvand, Demián García-Violini, John V. Ringwood
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Abstract

Considerable testing and modeling are required in order to fully realise, efficiently develop, and successfully industrialise the wave energy converters (WECs). Numerical modeling, full-scale measurements, and scaled prototype testing are the various methodologies that can be applied to model WECs and predict the dynamic response. Mathematical WEC models form the basis of model-based energy maximising control and directly affect the ability of model-based controllers to maximise energy capture. Linear WEC models are attractive in leading to simpler control designs, but may not cover the complete operational space. One solution is to identify a range of linear models at different operating points, which give a measure of the underlying nonlinear behaviour [1], [2]. This model set can then be used to extract a nominal model, and an associated uncertainty region, which can be used as a basis for a robust WEC controller synthesis process, such as articulated in [3]. Recently, such an approach has been adopted using data generated from a high-fidelity numerical computational fluid dynamics (CFD) model [4]. However, numerical wave tanks (NWTs) and physical wave tanks differ significantly in terms of the range of tests which can be performed, and the contamination which can affect the measurements used to determine the data-based models e.g. measurement noise, numerical effects, wave reflections, etc [5]. As a result, the determination of nominal models and uncertainty regions in a physical wave tank may provide some advantages (and disadvantages) which need to be examined carefully. In addition, the range of post-processing techniques which could, or should, be applied to the different experimental/numerical domains, to improve the fidelity of the identified models, may differ between domains. In this paper, experimental testing of a WEC, by recreating a wave field similar to real-life conditions and a small-scale version of the device, is used to understand the hydrodynamic behaviour and to obtain an accurate dynamic model for WECs, which are considered to be essential towards optimal WEC design. Physical wave tank experiments, even though having their own disadvantages, overcome some difficulties of CFD-based NWT experiments, most notably huge computation time, problems in accurate representation of viscous fluids, uncertainty in the specification of an appropriate turbulence model, and propagation of incident waves [6].  In this study, representative linear models of a point-absorber type WEC from a physical wave tank in the wave basin at Aalborg University are determined which give insight into the system dynamics and provide a basis for robust control of WECs. Among different stimulation techniques to excite the system dynamics in physical wave tank tests, the particular types of excitation signals covering the complete range of frequencies and amplitudes of the system dynamics, while considering limitations on the range of excitation signals or the wave tank reflections, are adopted for the determination of representative linear models. Moreover, a full investigation is carried out to ascertain the appropriate post-processing needed to optimise the signals as the basis for model identification. The model identification includes the non-parametric frequency response by means of empirical transfer function estimate (ETFE).   
从实验数据量化线性波能水动力模型的不确定性
为了充分实现、有效开发和成功工业化波浪能转换器(WECs),需要进行大量的测试和建模。数值模拟、全尺寸测量和比例原型测试是各种方法,可以应用于模拟WECs和预测动态响应。数学WEC模型构成了基于模型的能量最大化控制的基础,并直接影响基于模型的控制器最大化能量捕获的能力。线性WEC模型在导致更简单的控制设计方面很有吸引力,但可能无法覆盖整个操作空间。一种解决方案是确定不同工作点的一系列线性模型,这些模型给出了潜在非线性行为的度量[1],[2]。然后,该模型集可用于提取标称模型和相关的不确定性区域,这些区域可作为鲁棒WEC控制器合成过程的基础,如[3]中所述。最近,这种方法被采用,使用高保真数值计算流体力学(CFD)模型生成的数据[4]。然而,数值波槽(NWTs)和物理波槽在可进行的测试范围以及可能影响用于确定基于数据的模型的测量的污染方面存在显著差异,例如测量噪声、数值效应、波反射等[5]。因此,确定物理波槽中的标称模型和不确定区域可能会提供一些需要仔细检查的优点(和缺点)。此外,为了提高已识别模型的保真度,可以或应该应用于不同实验/数值领域的后处理技术的范围可能在不同领域之间有所不同。在本文中,通过重建与现实条件相似的波场和小型设备,对WEC进行了实验测试,以了解WEC的水动力行为,并获得准确的动态模型,这被认为是优化WEC设计的关键。物理波槽实验虽然有其自身的缺点,但克服了基于cfd的NWT实验的一些困难,主要是计算时间庞大、粘性流体的精确表示存在问题、合适湍流模型的不确定、入射波的传播等问题[6]。在这项研究中,确定了来自奥尔堡大学波池物理波槽的点吸收型WEC的代表性线性模型,该模型可以深入了解系统动力学,并为WEC的鲁棒控制提供基础。在物理波槽试验中激发系统动力学的各种激励技术中,在考虑到激励信号范围或波槽反射的限制的情况下,采用覆盖系统动力学的完整频率和幅值范围的特定类型的激励信号来确定具有代表性的线性模型。此外,还进行了全面的调查,以确定优化信号作为模型识别基础所需的适当后处理。模型辨识包括利用经验传递函数估计(ETFE)来辨识非参数频响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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