We’re frequently asked how our unique insights help customers to detect threats before they become incidents. Today we are sharing another “Insight of the Week.” This one was generated by our Power Lines application.
Detected by Enview for Power Lines – UVM Module
What did Enview find?
Enview’s Utility Vegetation Management Module (part of the Enview for Power Lines application) automatically identified “Grow-in” and “Fall-in” vegetation across an electricity transmission network of a utility customer. Grow-in vegetation findings were then visualized in multiple distance bands from the conductors for ease of prioritization. Fall-in vegetation that could contact the conductor or fall within 6 feet was represented by red markers identifying the location of the danger trees.
Why is this important?
Major incidents, wildfires, and unplanned outages may result from contact or inadequate clearances between vegetation and power lines. Many federal, state, and local regulations are in place to mandate clearances. Power line operators monitor their networks continuously to ensure that they abide by these regulations and prevent incidents and outages. Yet doing so by walking or flying the lines and judging distances with the human eye is challenging. The ability to identify the exact location and clearances of high-risk vegetation early and at scale helps operators prioritize and address the problem areas. LiDAR-driven programs have helped reduce this concern but are constrained by heroic levels of manual data manipulation. Automation of 3D Geospatial Analytics through AI, machine vision, and parallel computing enables accurate and extremely fast identification of at-risk spans.
What actions were taken?
Knowing the exact location of Grow-in and Fall-in vegetation along with precise clearance distances to their power lines, the client can confidently optimize contractor schedules and work orders. Field crews are able to plan and execute work more efficiently by using intuitive visualizations of encroaching vegetation, color-coded by clearance distance. Moreover, the network in the example above passed through an environmentally sensitive area with multiple stakeholders concerned about the impacts of cutting trees. Armed with accurate analytics and intuitive visualizations, the utility can effectively engage with stakeholders early on. Lastly, the client can further use the Vegetation Module to detect changes over time to confirm that vegetation work has been completed or to track vegetation growth rates.