(Digital Presentation) Mechanically Driven Electromagnetic Energy Harvesting for Power System Sensing Applications
Authors: Dey Smita , Song Kiseong , Ju Heungjin , Hwangbo Seungwook , Ahn Ethan C 
Published: August 2024

Introduction

Energy harvesting is a process of producing energy or usable power from the environment. Among potential ambient energy harvesting sources, electromagnetic (EM) field offers the great promise for emerging power system applications. This is because EM energies are widely available around the current-carrying wires (busbars) that connect various power devices and equipment. Most previous works on EM energy harvesting were built upon AC transmission lines [1-5], whereas modern power systems are typically driven by renewable DC energy sources. In this work, a mechanically-driven, DC-based EM energy harvesting system is designed and implemented as a lab-scale prototype to ultimately power sensing devices in the power system.

Key Results:

The schematic diagram and the photograph image of the EM induction experimental setup are shown in Figures 1a) and 1b), respectively. The energy harvester consists of a high permeability (μ ~ 2300) ferrite toroidal coil (cross sectional area 760 mm2) that is placed below a DC conducting (copper) slab at a distance of 1 cm. According to the Faraday’s law of induction (Equation 1), the open circuit voltage is proportional to the time rate of change of the magnetic flux (dφ/dt). This work is sharply distinguished from other works because the time variant nature originates from the physical vibration without using the AC power source. As seen in the figure, the toroidal coil is directly attached to a vibrator, thus experiencing a light-to-moderate amount of vibration. Here, the copper slab emulates the busbar in the power system, and the vibrator represents a practical scenario where the energy harvester is exposed to mechanical, machinery, and other noise sources.
Figure 2 plots the open circuit voltage (VOC) as a function of the number of coil turns (N) for the experimental setup shown in Fig. 1. VOC was measured using a multimeter between two terminals of the coil for the maximum current of 3 A applied to the copper slab. As expected, a linear trend of VOC vs. N was observed with the VOC value as high as 51.4 mV for the case of 2,500 turns. Importantly, VOC is scalable to the value that is sufficiently high to drive most modern sensing devices because VOC is proportional to current (I). It is common that more than 100 A flows in the busbar of the power system, which escalates VOC to more than 1.7 V. The idea of increasing VOC by increasing current is confirmed in Figure 3; we repeated the experiments by lowering the current value in the copper slab, and obtained the linear trend line. Thus, both results shown in Figures 2 and 3 indicate a strong correlation of our energy harvester prototype with the EM theory. The maximum VOC value we obtained (51.4 mV) is separately shown in Figure 4 as a photograph image of the multimeter reading.
In Table 1, we estimated the VOC values that can be readily achievable in the power system that affords the busbar current of 300 A and/or the 10,000 coil turns. For example, as compared with a previous work [3] with VOC of 1.4 V for 30 A (AC), this work features VOC of about 2 V with the 30 A DC power source.

Significance:

This work demonstrates the possibility of newly developing an mechano-electromagnetic energy harvester for modern power systems. Taking full advantage of EM energies and vibration present in the power system, the proposed DC-sourced energy harvesting scheme can greatly facilitate development and adoption of various sensing/monitoring/diagnosis device technologies. This is because these devices will not require separate batteries or power sources; they will be easily powered using the electromagnetic energy and mechanical vibration.

References:

[1] Gupta, V., Kandhalu, A., & Rajkumar, R. (2010, June). In proceedings of the 6th Workshop on Hot Topics in Embedded Networked Sensors (pp. 1-6).
[2] Van Schalkwyk, J. A., & Hancke, G. P. (2012, May). In 2012 IEEE International Symposium on Industrial Electronics (pp. 1128-1135).

[3] Chen, M., Wang, M., Yu, H., He, G., Zhu, Y., Liu, Y., & Wang, G. (2018). IEEE Transactions on Industrial Electronics, 65(11), 8956-8965.
[4] Roscoe, N. M., & Judd, M. D. (2013). IEEE Sensors Journal, 13(6), 2263-2270.
[5] Chang, K., Kang, S., Park, K., Shin, S., Kim, H. S., & Kim, H. (2012). Journal of Electrical Engineering & Technology, 7(1), 75-80.

Figure 1