PacifiCorp uses Technosylva to advance their data-driven decision-making for wildfire risk reduction and fire behavior simulation modeling. They’ve developed a new meteorological and wildfire safety department to improve their understanding of wildfire consequences, its impacts across its multi-state service areas, and risk mitigation priorities by:
- Installing thousands of miles of covered wires, fire-resistant poles and more
- Expanding their vegetation management practices to address emerging risks
- Integrating advanced technology and a dedicated meteorology team to better understand weather’s impact on their system and respond in real-time
Decades of Data Will Help Rocky Mountain Power Better Predict Wildfires
Rocky Mountain Power is a division of PacifiCorp and part of Berkshire Hathaway Energy
”New technology gives a 30-year hourly weather history and mixes that with today’s data to predict dangers, outages, and wildfires.Steve VanderburghRMP Meteorology Manager
Data-Driven Decision Making
To enable Pacific Power’s evolution to a quantified risk assessment model, in 2023 the Company initiated implementation of Technosylva’s Wildfire Platform.
The platform is used to perform wildfire modeling and risk analysis that calculates metrics, including the probability of an ignition from a utility asset given certain conditions, the potential spread of a wildfire, and the consequences of a fire including potential acres burned, population impacted, number of buildings threatened, and estimated number of buildings destroyed.
Incorporating Historic Weather for Ignition Risk
Pacific Power uses Technosylva to calculate the historical weather days that best represent when weather and fuel conditions can lead to an increased risk of ignition. This will enable Pacific Power to move to an annual cadence to capture new days that should be incorporated into the historical weather to account for changing weather conditions and vegetation over time.
Technosylva’s modeling capabilities, with meteorology team help, informs decision-making processes during PSPS events.
Improving and Ensuring Accurate Fuels Data
Fortunately, Technosylva is able to test this data, and other fuels data including their custom data, operationally on a daily basis with CAL FIRE and the IOUs against active wildfires to see how it performs.
Technosylva continually tests new fuels datasets that become available from other sources, such as LANDFIRE, federal risk assessment regional projects, and independent sources, such as the California Forest Observatory data. Unfortunately, the publicly available data does not perform at the level required when confronted with operational testing. In general, these publicly available data do not result in fire behavior outputs that facilitate accurate predictions. Ultimately with any fuels dataset, the quality and accuracy of the fuels is measured on whether it produces ‘observed and expected fire behavior’.