Wildfire Risk Grid De-Energization

AI models identify and protect must-run circuits during de-energization events. This ensures continuous power for:

• Hospitals, fire stations, and emergency services
• Water pumping and treatment facilities
• Communications towers and data centers By maintaining these lifelines, utilities uphold community safety and avoid secondary crises, preserving public trust and meeting regulatory mandates for critical infrastructure resilience.

AI-driven forecasting provides utilities with a 48-72 hour lead time on potential shutoffs. This enables automated, hyper-targeted customer communications via SMS, email, and IVR, specifying likely outage windows. Benefits include:

• Reduced call center volume by up to 40% through proactive alerts
• Improved customer satisfaction scores (CSAT) during high-stress events
• Allows customers and businesses (like hospitals and data centers) to activate backup generation, reducing community-wide disruption.

Once the high-risk period passes, AI accelerates the safe re-energization process. It analyzes post-event weather data, patrol reports, and drone imagery to create a prioritized restoration sequence. This delivers:

• Faster power restoration by optimizing crew dispatch
• Enhanced safety by ensuring lines are clear of damage before re-energization
• Operational cost savings by reducing unnecessary manual patrols and inspection time.

AI analyzes de-energization event data to identify chronic high-risk circuits. This provides a data-evidenced business case for capital investment in grid hardening, such as:

• Undergrounding priority lines
• Installing rapid earth fault current limiters
• Vegetation management program optimization This shifts spending from reactive liability management to proactive risk reduction, maximizing the ROI of grid modernization budgets and creating a more resilient asset base.

Objective: Expand AI coverage to the entire service territory and optimize the PSPS program for minimal customer impact.

• Tactical Scaling: Deploy models across all distribution circuits, accounting for localized vegetation, infrastructure age, and micro-climates.
• Advanced Optimization: Use AI to perform 'sectionalizing' analysis, identifying the smallest possible grid segments to de-energize to isolate risk. This can reduce affected customers by 60-70% per event.
• ROI Realization: Directly translates to lower Customer Interruption (CI) costs, reduced regulatory penalties for overly broad outages, and strengthened community trust. Enables predictive staging of mobile generation and customer resource centers.

Objective: Move beyond reactionary shutoffs to actively reducing the grid's ignition risk profile.

• Predictive Maintenance: AI pinpoints specific 'high-probability failure points' (e.g., a deteriorating insulator in a high-risk zone) for prioritized replacement before the fire season.
• Vegetation Management 2.0: Couple risk forecasts with satellite and LiDAR data to create hyper-accurate trim schedules, focusing capital and labor on the highest-risk corridors.
• Strategic Value: Transforms the PSPS program from a cost center into a capital planning tool. Reduces the frequency and duration of future shutoffs, delivering continuous year-round value and contributing to long-term wildfire mitigation capital deferral.

CIO Justification Framework: Frame the investment against concrete financial and risk metrics.

• Cost Avoidance: Model liability exposure from a single catastrophic fire (potential billions) against the AI program cost (millions).
• Regulatory Incentives: Many state commissions now allow cost recovery for grid hardening and advanced mitigation technologies; a robust AI program strengthens rate case arguments.
• Operational Savings: Reduce PSPS-related overtime, customer compensation payouts, and insurance premiums.
• Example ROI Calculation: For a mid-sized utility, a 30% reduction in affected customers per PSPS event can save $5-10M annually in direct costs, not including avoided liability.

Key to Success: Securing buy-in from the siloed departments that own pieces of the wildfire risk puzzle.

• Grid Operations: Needs real-time, actionable alerts in their existing systems.
• Vegetation Management: Requires prioritized work plans that maximize risk reduction per dollar spent.
• Customer Service & Communications: Depends on accurate, location-specific outage forecasts to execute proactive customer notifications.
• Legal & Regulatory: Needs defensible, documented decision logic for commissions and courts.
• The AI Platform acts as the single source of truth, aligning all teams around a unified risk model and coordinated action plan, breaking down operational silos.