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An indoor power line based magnetic field energy harvester for self-powered wireless sensors in smart home applications

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  • Maharjan, Pukar
  • Salauddin, Md
  • Cho, Hyunok
  • Park, Jae Yeong

Abstract

In smart home system (SHS), various IoT sensors are widely used for monitoring and security purposes. In order to detect fires, heat, potential disasters in early stage, and ensure the safety of electricity, real-time online condition monitoring of indoor power line is necessary. However, these monitoring sensors depend on batteries, either replaceable or rechargeable, which are less economical, have limited life time, are environmentally hazardous, and complex to replace. Herein, we present an indoor power line based magnetic field energy harvester (IPLEH), as a sustainable and maintenance free power supply for self-powered wireless monitoring sensors in smart home applications. The proposed IPLEH harvests energy from the magnetic field induced by a current carrying conductor without electrically contacting the conductor, that are easily available in indoor power line system. The IPLEH device consists of ferrite split-core which can be easily installed on the existing power lines without cutting or disturbing the power supply. The experiment results show that the proposed IPLEH can deliver an average power density of 14.67 mWcm−3 (average power of 105.24 mW under the optimum load resistance of 230 Ω). In addition, different sensors applications such as temperature, humidity, human motion, and plant health, which are driven by the IPLEH, are successfully demonstrated. The wide applicability of the IPLEH and the experimental results are promising for the development of sustainable energy harvesters, that can be practically implemented in self-powered wireless monitoring systems for residential, commercial and industrial buildings.

Suggested Citation

  • Maharjan, Pukar & Salauddin, Md & Cho, Hyunok & Park, Jae Yeong, 2018. "An indoor power line based magnetic field energy harvester for self-powered wireless sensors in smart home applications," Applied Energy, Elsevier, vol. 232(C), pages 398-408.
  • Handle: RePEc:eee:appene:v:232:y:2018:i:c:p:398-408
    DOI: 10.1016/j.apenergy.2018.09.207
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    References listed on IDEAS

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    5. Yang, Ting & Zhao, Liyuan & Li, Wei & Wu, Jianzhong & Zomaya, Albert Y., 2021. "Towards healthy and cost-effective indoor environment management in smart homes: A deep reinforcement learning approach," Applied Energy, Elsevier, vol. 300(C).
    6. Qi, Nanjian & Yin, Yajiang & Dai, Keren & Wu, Chengjun & Wang, Xiaofeng & You, Zheng, 2021. "Comprehensive optimized hybrid energy storage system for long-life solar-powered wireless sensor network nodes," Applied Energy, Elsevier, vol. 290(C).
    7. Wang, Quan & Kim, Kyung-Bum & Woo, Sang Bum & Ko, Sung Min & Song, Yooseob & Sung, Tae Hyun, 2022. "Enhanced electrical performance of spring-supported magneto piezoelectric harvester to achieve 60 Hz under AC magnetic field," Energy, Elsevier, vol. 238(PB).
    8. 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).

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