Browsing by Author "Keprate, Arvind"
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Item Open Access Qualitative investigation of wake composition in offshore wind turbines: a combined computational and statistical analysis of inner and outer blade sections(EDP Sciences, 2024-02-06) Siddiqui, M. Salman; Badar, Abdul Waheed; Yang, Liang; Saeed, Muhammed; Keprate, ArvindHigh-fidelity numerical simulations are used to thoroughly analyze the evolution of the wake behind a megawatt-scale offshore wind turbine. The wake features are classified in terms of wake dynamics composition and the associated turbulence characteristics originating from the inner and outer sections of the blades. Understanding the wake is essential for developing compact layouts for future wind farms. We employed a transient Sliding Mesh Interface (SMI) technique to analyze the fully dynamic wake evolution of the offshore NREL 5MW full turbine. Our high-fidelity results have been validated against previously published results in the literature. We thoroughly investigated the dominant structures of the wake using Proper Orthogonal Decomposition (POD) techniques, which we applied to transient simulations of fully developed flows after five wind turbine revolutions over the snapshot data. Our findings show that the inner section of the blades, which is composed of airfoils with larger cross-sections, is responsible for the dominant components of the wake, while the contribution of the wake from the outer section of the blade is significantly lower. Therefore, designing more aerodynamic sections for the blade’s inner section can help reduce the dominant wake components and thus decrease the inter-turbine distance in future wind farms.Item Open Access Towards an integrative framework for digital twins in wind power(IEEE, 2024-02-01) Siddiqui, M. Salman; Keprate, Arvind; Yang, Liang; Malmedal, TirilThe present global climate crisis necessitates urgent integration of sustainable and renewable energy resources, coupled with digital technology. Renewable energy stands out as a viable solution, and among the various renewable energy sources, wind power is believed to play a crucial role in this transition. In the era of industrial digitalization, implementing smart monitoring and operation becomes a vital step toward optimizing resource utilization. Consequently, the application of Digital Twins (DT) emerges as a promising approach to enhance power output in the wind energy sector. DTs for energy systems encompass multiple areas of study, such as smart monitoring, big data technology, and advanced physical modeling. While several frameworks exist for structuring DTs, few standardized methods have been established based on the experience gained. To address this gap, the present research proposes an integrative development framework for DTs, tailored explicitly to the aerodynamics of wind turbines, to ensure their successful operation throughout the entire lifecycle, from aggregation to performing actions. A seven-step framework is presented, which identifies the potential components and methods required to create a fully developed DT.