SilverFern Power is founded by a group of experts and entrepreneurs specialized in power automation and modern communications in 2013. The company concentrates on improving the visibility and efficiency in power system through utilization of Internet of Things (IoT) and Big Data Analysis. SilverFern invests millions of US dollars in R&D every year.  Tens of thousands of smart grid sensors have been successfully deployed in Ultra High Voltage (UHV) system and medium voltage distribution network for real-time monitoring, power quality analysis, assets performance management, equipment failure diagnosing，distribution fault anticipation based early warnings, and fault detection and location.

Our Solution: LinePatrol® Smart Grid Sensor (SGS) + SFPlatform Cloud-based Big Data Analytical Platform

SGS is an inductively self-powered intelligent device, easy to install and maintenance free. Unlike the traditional power line sensors and FCIs, the wide-area timing synchronization and high-precision measurement are introduced in SGS. Providing previously unavailable critical information such as phasors, SGS helps utilities to gain visibility and improve efficiency for a more reliable grid. The operation cost can be greatly reduced. SFPlatform stores and analyzes all the data and event waveforms collected by SGSs and sends notifications of the faults, disturbances, exceptional unbalances and harmonics information immediately via SMS or APP. The system can be used to predict power failures and be extended to the distribution automation applications of Wide Area Monitoring Systems (WAMS) with dynamic line rating, power flows and line loss computation etc. to further increase the visibility of distribution grids. 
* 1us wide-area timing sync. err, 256 samples/cycle, 0.5 grade measurement
* Easy installation via hot stick, 5A line current at full operation
* High accuracy single-phase earth fault detection and location
* Suitable for various kinds of neutral grounding systems

SilverFern Power Technologies

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SilverFern Power Technologies

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