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A self-regulation blades wind energy harvester system for self-powered wireless monitoring sensors

doi: 10.1063/5.0215474
Using wind energy in the natural environment provides a promising solution for wireless sensor power supply for ecological, meteorological, environmental, and infrastructure monitoring. However, the uncertainty and disorder of natural wind restrict the further development of wind energy harvester systems and self-powered wireless sensor technology. Hence, this paper proposes a self-regulation blade wind energy harvester system (SBWEHS) for self-powered wireless monitoring sensors in remote field areas with power shortages. The system is mainly composed of three parts: wind harvesting mechanism, generator module, and energy storage module. The device can control the blade overlap ratio according to the wind speed while generating electricity to maximize the power coefficient. The system can control the blade’s closure in bad weather to protect the device. Based on the computational fluid dynamics technology of Ansys Fluent software, this study evaluated the impact of wind speed and blade overlap ratio on the two-stage blades. Experiments revealed that when the overlap ratio of the blades is fixed at 0.2 and the wind speed is set at 16 m/s, the maximum average power will reach 0.79 W, which fulfills the power requirements of wireless sensors. These results illustrate that the SBWEHS can effectively supply power for wireless monitoring sensors, especially in remote natural environments.
- Liaocheng University China (People's Republic of)
- Taiyuan University of Technology China (People's Republic of)
- Taiyuan University of Technology China (People's Republic of)
- Liaocheng University China (People's Republic of)
Physics, QC1-999
Physics, QC1-999
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).2 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
