Nonlinear Analysis and Closed-Form Solution for Overhead Line Magnetic Energy Harvester Behavior

Alexander Abramovitz, Moshe Shwartsas, Alon Kuperman

Research output: Contribution to journalArticlepeer-review

Abstract

Featured Application: Magnetic energy harvesting of an overhead line. Recently, much attention has been given to the development of various energy harvesting technologies to power remote electronic sensors, data loggers, and communicators that can be installed on smart grid systems. Magnetic energy harvesting is, perhaps, the most straightforward way to capture a significant amount of power from a current-carrying overhead line. Since the harvester is expected to have a small size, the high currents of the distribution system easily saturate its magnetic core. As a result, the operation of the magnetic harvester is highly nonlinear and makes precise analytical modeling difficult. The operation of an overhead line magnetic energy harvester (OLMEH) generating significant DC power output into a constant voltage load was investigated in this paper. The analysis method was based on the Froelich equation to analytically model the nonlinearity of the core’s BH characteristic. The main findings of this piecewise nonlinear analysis include a closed-form solution that accounts for both the core and rectifiers’ nonlinearities and provides an accurate prediction of OLMEH transfer window length, output current, and harvested power. Continuous and discontinuous operational modes are identified and the mode transition boundary is obtained quantitatively. The theoretical investigation was concluded by comparison with a computer simulation and also verified by the experimental results of a laboratory prototype harvester. A good agreement was found.

Original languageAmerican English
Article number9146
JournalApplied Sciences (Switzerland)
Volume14
Issue number19
DOIs
StatePublished - 1 Oct 2024

Keywords

  • magnetic cores
  • magnetic energy harvesting
  • magnetic flux
  • saturation magnetization

All Science Journal Classification (ASJC) codes

  • General Materials Science
  • Instrumentation
  • General Engineering
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes

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