Abstract
Vertical Axis Wind Turbines (VAWTs) are omnidirectional turbomachines commonly used in rural areas for small-to-medium-scale power generation. The complex flow observed in the wake region of VAWTs is affected by a number of factors, such as rotor blades design. A damaged rotor significantly alters the flow field in the wake region of the VAWT, degrading its power generation capability. Published literature on damaged wind turbine blades is severely limited to torque signal analysis and basic flow field description in the wake region. In this study, detailed numerical investigations have been carried out to establish and quantify the relationship between damaged rotor and the wake dynamics of a VAWT. Time-based Computational Fluid Dynamics analyses have been performed on two VAWT models, one undamaged and the other with a missing rotor blade. Proper Orthogonal Decomposition has been used to extract the energy content and temporal coefficients of the various flow patterns associated with the wake region. The results indicate that the first pressure-based flow mode contains 99% of the energy and provides a functional basis for accurate reconstruction of the wake. It is envisaged that this study will aid the development of novel machine learning algorithms for rotor damage detection in wind farms.
Subject
Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous)
Cited by
6 articles.
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