“Regional assumptions are outdated. Every electric utility, regardless of location, must be prepared for compound weather risk and multi-hazard disruption.”
For decades, electric utilities have relied on seasonal planning, historical averages, and static risk assessments to guide grid resiliency decisions. That era is over.
Today’s threat landscape moves faster than traditional tools can track. Wildfires ignite outside of fire season. Other extreme weather events, like flooding, overtake grid infrastructure. Wind events cripple urban service territories. And the expectations from regulators, insurers, and investors are shifting just as fast.
In a recent POWER Magazine webinar, leaders from CenterPoint Energy and Technosylva offered a firsthand look at how AI, machine learning, and real-time weather modeling can be embedded into grid strategy. The message was clear: electric utilities must evolve from risk awareness to risk accountability, and fast.
Wildfire and Extreme Weather Risk Is Local, But the Shift Is Industry-Wide
CenterPoint Energy’s service territory is not traditionally viewed as wildfire territory. Yet FEMA’s wildfire risk map revealed that Harris County has more wildfire-prone census tracts than any other county in the country.
This single insight reframed their resilience planning. It also underscored a larger truth: regional assumptions are outdated. Every electric utility, regardless of location, must be prepared for compound weather risk and multi-hazard disruption.
AI-Powered Modeling Changes What’s Possible
Technosylva’s platform simulates wildfire and extreme weather scenarios using real-time data and advanced weather forecasts. For electric utilities, that means:
- Forecasting outage severity days in advance
- Calculating risk at the circuit level
- Prioritizing grid hardening where the data shows it matters most
- Improving restoration timelines and customer communication
This is not theoretical. Don Daigler, Senior Vice President of Emergency Preparedness and Response at CenterPoint Energy, shared that modeling is helping CenterPoint estimate how many crews they may need, how long restoration could take, and where to place staging areas based on forecasted conditions.
From Resilience to Regulatory Alignment
AI and modeling are not just about mitigation. They are fast becoming the foundation of regulatory and financial credibility.
Regulators are asking more pointed questions. Credit rating agencies want to see data-backed resilience plans. Insurers are tightening coverage, if they offer it at all. Stakeholders at every level are demanding more than good intentions. They expect electric utilities to demonstrate readiness with operational data.
The implications are clear: resilience strategy is no longer internal. It is visible, judged, and tied directly to access to capital, regulatory standing, and public trust.
Looking Ahead: Integration Is the Imperative
Leading electric utilities are doing more than evaluating software or building dashboards. They are integrating modeling into core operations, breaking silos between emergency preparedness, asset planning, and enterprise risk. They are training operators on live situational awareness and modeling impact. And they are aligning their planning with regulatory frameworks from day one.
The next phase of utility resilience is not about adopting a tool. It is about building a system of accountability that is driven by real-time intelligence and aligned with what is at stake – financially, operationally, and reputationally.
Watch the webinar replay below to get more depth from the conversation
