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Hybrid energy harvesting for condition monitoring sensors in power grids

Author

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  • Yang, Feng
  • Du, Lin
  • Chen, Weigen
  • Li, Jian
  • Wang, Youyuan
  • Wang, Disheng

Abstract

In this paper, we present a novel hybrid scheme of magnetic, thermoelectric, and vibration energy harvesting (EH) system, which is directed towards the low-power sensing applications within power grids. The topology aims to address the energization of wireless sensor networks that are deployed for the condition-based monitoring purposes of electric facilities. To this end, we have investigated the energy conversion properties of the three EH modalities by means of simulation studies and in-lab experiments. Thereafter, a hybrid energy management system has been established using an ultra-low power consumption circuitry to regulate and integrate individual outputs from the front-end harvesters. During a proof-of-concept, we have observed from a developed demonstrator that a DC output voltage held steady and the output was fed into a ZigBee sensor to keep it operational meanwhile without downtime, which indicates that the power consumption of a ZigBee node can be fully covered by the harnessed energy in the context of this article. Hence, the ambient energy scavenging methodologies discussed herein are well-suited to empower energy-autonomous sensors. The work is characterized by the first demonstration of thorough assessment of the three stray energy forms in the grid and the joint utilization thereof to enhance the system loading capacity. Rather than exploiting a single ambient energy source of some kind, this hybrid and versatile option is proven to accomadate more stable power throutput, and the system signifies feasibilities and potentials to improve the problematic power supplies of the sensors that are deployed within the grid.

Suggested Citation

  • Yang, Feng & Du, Lin & Chen, Weigen & Li, Jian & Wang, Youyuan & Wang, Disheng, 2017. "Hybrid energy harvesting for condition monitoring sensors in power grids," Energy, Elsevier, vol. 118(C), pages 435-445.
  • Handle: RePEc:eee:energy:v:118:y:2017:i:c:p:435-445
    DOI: 10.1016/j.energy.2016.11.037
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    3. Lineykin, Simon & Maslah, Kareem & Kuperman, Alon, 2020. "Manufacturer-data-only-based modeling and optimized design of thermoelectric harvesters operating at low temperature gradients," Energy, Elsevier, vol. 213(C).
    4. Kosunalp, Selahattin, 2017. "An energy prediction algorithm for wind-powered wireless sensor networks with energy harvesting," Energy, Elsevier, vol. 139(C), pages 1275-1280.
    5. Kuang, Yang & Chew, Zheng Jun & Ruan, Tingwen & Lane, Tim & Allen, Ben & Nayar, Bimal & Zhu, Meiling, 2021. "Magnetic field energy harvesting from the traction return current in rail tracks," Applied Energy, Elsevier, vol. 292(C).
    6. Liu, Huicong & Fu, Hailing & Sun, Lining & Lee, Chengkuo & Yeatman, Eric M., 2021. "Hybrid energy harvesting technology: From materials, structural design, system integration to applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).

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