LineVision | Technology (2024)

LineVision Methodologies

LineVision LUX

Welcome to a new era in power line sensing with LineVision LUX™, where insight meets innovation. Just as lux represents the SI unit of illuminance, our technology illuminates opportunities previously hidden in the grid for increased capacity and line health visibility.

Non-contact sensor eliminates the need for expensive installation equipment, high-risk work for line crews, or outages

LiDAR technology can monitor all phases of multiple circuits, even bundled conductors, with just one sensor

Sensors collect granular, real-world data in real-time, which train and validate LineVision methodologies

Stainless steel enclosure and long-lasting Lithium Iron Phosphate (LiPO4) battery ensure lifetime reliability

Plug-and-play wiring and modularized assembly increase installation efficiency and ease

Rigorously tested in harsh environmental conditions, assembled in the USA, with a full hardware maintenance warranty for life of contract

Specifications

Weight

2.04 lbs (0.93kg)

Ingress Protection Rating

IP67

LiDAR Sensor Accuracy

+/- 3 cm at up to 200 m distance

Corrosion Rating

MIL-STD-810H Method 509.7

Weight

30.3 lbs (13.7 kg)

Ingress Protection Rating

IP66

Assembly

Plug-and-play wiring, modularized assembly, 304 stainless steel

Corrosion Rating

MIL-STD-810H Method 509.7

Type

Lithium Iron Phosphate (LiFePO4)

Weight

13.7 lbs (6.2 kg)

Nominal Voltage/Capcity

12.8 V / 52 Ah

Integrated Protections

Over-voltage, under-voltage, temperature limit detection

Weight

12 lbs (5.5kg)

Ingress Protection Rating

IP65

Maximum Power

100 W @ 12 V

Voltage at Max Power

19.8 V

Current at Max Power

5.06 A

Tower Compatibility

Lattice towers, monopoles; adaptable platform mounting brackets

Product Assembly

All LineVision products are assembled in the USA in an ISO 9001 certified environment

Warranty

Full hardware maintenance and warranty for life of contract

Conductor Compatibility - AC and HVDC

No conductor size or voltage restrictions

Methodologies

Developed and refined by LineVision’s industry-leading meteorologic and data science teams, our state-of-the-art methodologies employ techniques in machine learning and computational fluid dynamics (CFD) modeling, along with real-time sensor measurements including sag and blowout to build a comprehensive, validated, and safe model to calculate wind speed, and ultimately a DLR.

Dynamic Line Ratings Methodology

LineVision's sensor-validated Dynamic Line Ratings (DLR) are calculated using a combination of precisely modeled and measured data inputs. Weather data and computational fluid dynamics are used to account for hyper-local terrain and vegetation along the transmission corridor. The model is then trained using machine learning and LineVision LUX inputs of sag, blowout, and conductor temperature. This approach enables LineVision to determine the true ampacity of the line with a high level of accuracy. The DLRs are then delivered in real-time and hourly forecasts up to 10 days ahead.

Situational Awareness Methodology

LineVision’s LineAware solution uses the LineVision LUX sensor to ingest real-time field measurements of conductor sag and blowout to build a digital twin model of the monitored transmission span. The LineAware solution ensures lines are within safe operating limits with real-time alerting on anomalous horizontal and vertical conductor position on each phase of power as well as icing risk and detection.

Asset Health Methodology

LineVision’s LineHealth solution builds a digital twin of the monitored transmission span to help engineers prioritize the repair and replacement of lines that are identified as critical or at risk. The solution ingests data from the LineVision LUX sensor to monitor real-time conductor behavior and model end of life projections, sag distributions, conductor elongation, aeolian vibration risk, and projects the safe maximum operating temperature.

By applying a multi-layered and sensor-based approach, the data models within each of our software offerings are continuously trained and validated, resulting in the most reliable DLR and transmission line analytics available.