- Fault Detection & Location
- Preventive Analysis
- Improved Grid Reliability and Safety
- Compatible with 50Hz/60Hz grids
- High precision current measurement up to 630A
- High sampling rate of oscillograph waveforms: 256 samples/cycle
- Zero-sequence current synthesis enabled by 20μs precision sync
- Cloud-based server
- AI Analytics Platform
- GIS-based real-time monitoring of line status and events
- Deep learning analytic system
- Oscillography waveform classification powered by AI algorithms
- Accurate fault location and SMS alarms
- Preventive analysis and early warning
- Flow Direction & Load Analysis
Overhead Line Power Network Diagnostic System Based on Artificial Intelligence (AI)
Overhead Line Fault Indicators are usually used in radial medium and high voltage overhead line distribution networks, which neutral points are ineffectively grounded.
Traditionally utilities use fault detection sensors in every phase of the overhead lines to detect short-circuit fault and single-phase earthed fault. The sensor will flag with a blinking LED when there is fault on the lines. This measurement faces many challenges to find exact location and cause of the fault especially on difficult terrain such as mountains or forest as well as on severe conditions such as heavy rain or typhon. Those situations caused a longer time to find faults and decide to block the fault lines.
Wireless overhead-line system is developed to detect, locate faults and events for distribution overhead line and to enable advanced grid analytics with precise and rich information from voltage & current waveforms. The system is composed of three parts: the sensors mounted on the line, the concentrator as a communication unit, and a cloud-based headend system to do analytics with AI technology.
The sensors are installed along the overhead line, to monitor the voltage and current. If any events or faults occurs on the line, all the sensors belonging to the same busbar will sense the voltage and current change and be triggered to record an oscillograph waveform. These waveforms are uploaded by using wireless communication to the headend system and analysed with AI-enabled algorithms to locate the fault. The analytics results will be sent to the line patrol team with SMS to guide them to find the location of the fault quickly.
The sensors also indicate the fault by flashing three ultra-bright blinking LEDs, which can be seen from 360º sight. The fault information and load current value can also be transmitted to the SCADA by 2G/3G/4G networks.
With this system, utility companies can easily find the fault location and make decisions to manoeuvre the fault lines faster.
- Model
- Categories
- Internet of Things
- Brand
- LINE SENSORS
- Compatible with 50Hz/60Hz grids
- High precision current measurement: 0~630A, ±0.5%
- High sampling rate of oscillography waveforms: 12.8KHz (256 samples/cycle)
- Zero-sequence current synthesis enabled by 20μs precision sync
- Power optimization operation
- Full-function mode: all functions including waveform recording enabled; Powered by line and supercapacitor
- Low-power mode: waveform recording disabled; powered by line and battery
- Power harvesting: 1A to support full-function mode; supercapacitor backs for 12h
- IP67, water proof
- Light weight: <1.5kg, live installation and removal
- CONCENTRATOR
- WAN: LTE/AMI/LoRa
- Field Area Network: RF
- High-Precision (1μs) GPS for location and time synchronization
- Fault detection based on zero-sequence current synthesis
- Main and backup power: solar, maintenance-free capacitor
- IP55 protection
- Remote upgrade & maintenance
- AI ANALYTICS PLATFORM
- Sensor and concentrator management
- GIS-based real-time monitoring of line status and events
- Deep learning analytic system
- Oscillography waveform classification powered by AI algorithms
- Accurate fault location and SMS alarms
- Preventive analysis and early warning
- Flow Direction & Load Analysis
- Reports
- Load trend & statistics
- Power quality analysis
- Fault statistics
- Overhead Medium Voltage Power Line / Grid


