Abstract
With the development of intelligent modern power systems, real-time sensing and monitoring of system operating conditions have become one of the enabling technologies. Due to their flexibility, robustness and broad serviceable scope, wireless sensor networks have become a promising candidate for achieving the condition monitoring in a power grid. In order to solve the problematic power supplies of the sensors, energy harvesting (EH) technology has attracted increasing research interest. The motivation of this paper is to investigate the profiles of harnessing the electric and magnetic fields and facilitate the further application of energy scavenging techniques in the context of power systems. In this paper, the fundamentals, current status, challenges, and future prospects of the two most applicable EH methods in the grid—magnetic field energy harvesting (MEH) and electric field energy harvesting (EEH) are reviewed. The characteristics of the magnetic field and electric field under typical scenarios in power systems is analyzed first. Then the MEH and EEH are classified and reviewed respectively according to the structural difference of energy harvesters, which have been further evaluated based on the comparison of advantages and disadvantages for the future development trend.
Highlights
Emerging technologies in power systems such as smart grid (SG) and ubiquitous power Internet of things (UPIOT) have attracted considerable interest recently [1,2,3]
According to the different patterns of controlling the energy delivered from the primary side to the loading side, high-potential magnetic field energy harvesting (MEH) methods can be classified into three types: improved Rogowski coil, current-limiting current transformer (CT) and compensative CT
This paper provides a review of the investigations on electric field energy and magnetic field energy harvesting for achieving energy-autonomous condition monitoring sensors or devices in the power grid scenario
Summary
Emerging technologies in power systems such as smart grid (SG) and ubiquitous power Internet of things (UPIOT) have attracted considerable interest recently [1,2,3]. Since the large-scale networks are expected to be mostly manipulated “intelligently”, massive and real-time information needs to be collected, in particular the parameters associated with critical power equipment, which enable the smart-grid to respond to changing conditions proactively Such parameters may be associated with the operational conditions (e.g., voltage, current), or the meteorological factors at the deployed site (e.g., temperature, humidity) [4,5]. The magneto-mechano-triboelectric generator was designed using piezoelectric and magnetostrictive materials, which convert magnetic noise to useful electric energy applying for low-power consuming electronics or wireless sensor networks [17,18,19]. From the perspective of available resources, there are many location-dependent sources of harvestable energy in the context of a power grid, such as solar, electric field, magnetic field, thermoelectric and vibration-based energy.
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