波浪能变换器优化设计中鲁棒性与不确定性分析的相关性

Filippo Giorcelli, S. Sirigu, Dario Basile
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引用次数: 0

摘要

波浪能转换器的优化设计以降低该技术的能源成本是一个被广泛研究的课题。在文献中,经典的优化策略已经被提出并应用于确定WECs的最优系统参数,以优化特定的技术经济指标。最优识别设备的性能依赖于这些标称参数,并且可能受到结构和建模不确定性的强烈影响。在这种情况下,最优解的鲁棒性概念在识别其性能受各种不确定性影响尽可能小的设备方面起着相关作用。在本文的第一部分中,从其他应用领域中推导出鲁棒性概念的不同变体并进行了描述。然后将识别的鲁棒性指标应用于通过经典优化获得的最优解,以评估其在WECs设计过程中的重要性。与这种方法严格相关的是灵敏度分析(SA)技术,其目的是研究输入变化(由于不确定性或外部噪声或额外的环境参数)如何影响已定义的数值模型的输出结果,并突出相对输入参数的相关性。因此,敏感性分析可以成为一种有价值的工具,适用于不确定性集估计,以识别最受这些不确定性影响的变量及其显著性。这项工作的主要目的是强调在优化过程中引入WECs鲁棒性评估的重要性,因为经典的优化技术可能导致受不确定性影响的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Relevance of Robustness and Uncertainties Analysis in the Optimal Design of Wave Energy Converters
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.
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