Spatial Optimization and LiDAR for Vermont Energy Resilience (SOLVER)
Abstract
Electrical Grid Utility providers spend time and money on maintaining the reliability and resilience of their grid systems; electrical grid distribution utilities have limited resources for maintaining vegetation. New statewide LiDAR collects of Q1 quality data are high enough resolution to assess vegetation risk to distribution grids, allowing for risk assessments to grid resilience at lower cost to utility providers. Contingencies were created based on these risk metrics and simulated using Transmission & Distribution Co-Simulation, identifying the severity of potential outages and proliferation of upstream effects within distribution feeders and transmission systems.
Primary Faculty Mentor Name
Dana Rowangould
Status
Graduate
Student College
College of Engineering and Mathematical Sciences
Program/Major
Electrical Engineering
Primary Research Category
Engineering and Math Science
Spatial Optimization and LiDAR for Vermont Energy Resilience (SOLVER)
Electrical Grid Utility providers spend time and money on maintaining the reliability and resilience of their grid systems; electrical grid distribution utilities have limited resources for maintaining vegetation. New statewide LiDAR collects of Q1 quality data are high enough resolution to assess vegetation risk to distribution grids, allowing for risk assessments to grid resilience at lower cost to utility providers. Contingencies were created based on these risk metrics and simulated using Transmission & Distribution Co-Simulation, identifying the severity of potential outages and proliferation of upstream effects within distribution feeders and transmission systems.
