Overview
SDG&E uses Technosylva to develop fire behavior modeling and simulations for enhanced PSPS decision-making. SDG&E is also advancing its own WiNGS-Planning model with Technosylva platforms to define wildfire consequence.
A wildfire risk analysis report published this year by the California Public Utilities Commission’s Safety and Enforcement Division found that PSPS carried out by SDG&E between Oct. 10 and Nov. 1, 2019, possibly prevented utility-related wildfires which could have had the potential to affect up to 34,471 people, damage 35,112 buildings and burn approximately 327,277 acres.
- 15th consecutive year without a catastrophic utility-caused wildfire
- 93% reduction vegetation-related ignitions
- 62% reduction vegetation related faults
- 83% reduction in faults on transmission circuits
- 65% reduction in faults on covered conductor distribution circuits
San Diego Gas & Electric (SDG&E) recently unveiled its wildfire mitigation and resiliency advancements.
Improving PSPS Decision Making
The likelihood of a PSPS event occurring is determined using several probabilities of a PSPS event being initiated on that segment. This model was developed by Technosylva and consists of outputs relating to buildings, acres, and population affected based on numerous model simulations using SDG&E assets as ignition points. In addition to the affected conditions, attributes such as fire behavior index and flame length are also provided to gauge wildfire spread.
SDG&E has been approaching the undergrounding project by first focusing on areas with higher historical power outages, extreme weather patterns and risk for wildfire.
Fire Behavior Modeling
SDG&E uses Technosylva for fire spread simulations. Simulations are based on the 141 worst historical fire weather days and simulate ignitions at regular intervals along the electric distribution system. The FireSight model is used to understand the relative consequences of wildfire and inform mitigation decisions.
SDG&E benefits from fire behavior modeling that is validated by CAL FIRE use of the Technosylva platform and direct feedback and cooperation with Technosylva on model and data updates.
