Aerodynamic Performance and Impact Analysis of a MEMS-Based Non-Invasive Monitoring System for Wind Turbine Blades
Wind power generation plays a crucial role in transitioning away from fossil fuel-dependent energy sources, contributing significantly to the mitigation of climate change. Monitoring and evaluating the aerodynamics of large wind turbine rotors is crucial to enable more wind energy deployment. This i...
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Main Authors | , , , , , , , , |
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Format | Journal Article |
Language | English |
Published |
21.08.2024
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Online Access | Get full text |
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Summary: | Wind power generation plays a crucial role in transitioning away from fossil
fuel-dependent energy sources, contributing significantly to the mitigation of
climate change. Monitoring and evaluating the aerodynamics of large wind
turbine rotors is crucial to enable more wind energy deployment. This is
necessary to achieve the European climate goal of a reduction in net greenhouse
gas emissions by at least 55% by 2030, compared to 1990 levels. This paper
presents a comparison between two measurement systems for evaluating the
aerodynamic performance of wind turbine rotor blades on a full-scale wind
tunnel test. One system uses an array of ten commercial compact ultra-low power
micro-electromechanical systems (MEMS) pressure sensors placed on the blade
surface, while the other employs high-accuracy lab-based pressure scanners
embedded in the airfoil. The tests are conducted at a Reynolds number of 3.5 x
10^6, which represents typical operating conditions for wind turbines. MEMS
sensors are of particular interest, as they can enable real-time monitoring
which would be impossible with the ground truth system. This work provides an
accurate quantification of the impact of the MEMS system on the blade
aerodynamics and its measurement accuracy. Our results indicate that MEMS
sensors, with a total sensing power below 1.6 mW, can measure key aerodynamic
parameters like Angle of Attack (AoA) and flow separation with a precision of
1{\deg}. Although there are minor differences in measurements due to sensor
encapsulation, the MEMS system does not significantly compromise blade
aerodynamics, with a maximum shift in the angle of attack for flow separation
of only 1{\deg}. These findings indicate that surface and low-power MEMS sensor
systems are a promising approach for efficient and sustainable wind turbine
monitoring using self-sustaining Internet of Things devices and wireless sensor
networks. |
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DOI: | 10.48550/arxiv.2408.11458 |