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FireRisk™ integrates advanced weather forecasts with WFA FireSim™ modeling to perform hundreds of millions of fire simulations daily to derive both current and near-term risk forecasts for customer service territories and critical assets. New forecasts are derived daily, sometimes twice a day, to provide accurate and timely analysis of possible wildfire events.
Baseline risk and consequence metrics are derived by identifying at-risk populations, buildings, and critical facilities that may be impacted. For electric utility customers, risk metrics are calculated hourly for infrastructure assets to support possible PSPS de-energization analysis, as well as EOC activation, stakeholder and public notification, and resource allocation and deployment.
Advanced analysis is undertaken to estimate the number of buildings destroyed or severely damaged if a wildfire were to occur. This advanced analysis leverages the rich historical data repository developed by Technosylva and employed in Machine Learning models to accurately analyze potential building loss.
Technosylva customers include leaders such as:
FireRisk’s outputs provide the foundation for wildfire risk analysis, through enhanced consequence modeling to quantify safety, financial and reliability metrics consistent with enterprise risk management methods. For electrical utility, risk metrics are assigned back to potential asset ignition sources identifying which assets are of most concern, in what areas. The integration of fire spread modeling provides information not readily available in the past, and is a key ingredient for distinguishing those assets prime for de-energization or mitigation. For wildfire management agencies, risk forecasts identify people, assets and critical facilities at risk providing the information necessary for resource prioritization and response planning.
Assets that are possible ignition sources, such as powerlines, are analyzed with wildfire spread predictions and probability of ignition models to identify those assets which will have the greatest impacts, should they cause an ignition. This information is a key ingredient for the PSPS decision making process.
Risk is calculated continuously across the entire service territory by analyzing spread impacts from regularly spaced ignition points. This information is ideal for setting agency readiness levels, staging resources and prioritizing areas of concern.
A key metric is identifying fire size potential for possible wildfires should they occur. This metric identifies areas where fires will grow quickly given specific weather and fuel conditions.
Building footprints are used to identify structures most at risk given weather conditions & potential fire behavior. Estimates of buildings threatened and possibly destroyed are derived leveraging advanced Machine Learning models and rich historical loss data. Loss is assessed on an individual building basis providing highly granular data to support decision making, whether you are a response agency, electrical utility company, or insurance company.
Public safety during wildfire events is paramount. Detailed population data is employed in the wildfire risk models to identify population at risk and support evacuation planning across the customer territory. Advanced models are applied to identify social vulnerability and egress concerns that may increase risk in certain areas.
Technosylva is the leading provider of wildfire risk mitigation solutions protecting communities and assets from the devastating effects of wildfires
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