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Utilities operating in wildfire-prone regions face a growing challenge: the risk of power line-related ignitions and presence of flammable vegetation.

A Strategic Approach to Wildfire Risk Mitigation

May 30, 2025
A proactive strategy integrates advanced technology, predictive modeling, data-driven decision-making and adaptive infrastructure planning.

Wildfire risk management is becoming an increasingly critical priority for electric utilities as they seek to safeguard communities, protect infrastructure and maintain uninterrupted service. The growing threat of wildfires calls for a clear, strategic approach to mitigation and resilience. Climate change and the expansion of wildland-urban interface (WUI) areas have further intensified these risks, both the frequency and severity of wildfire events. Proactive strategies are essential for preventing fire ignitions and minimizing the operational, financial, and regulatory risks associated with wildfires.

By integrating system hardening, targeted vegetation management and advanced protection technologies with predictive analytics in the form of a wildfire risk mitigation model, utilities can create a robust strategy to mitigate wildfire risk. These measures not only reduce the likelihood of power line-related wildfires but also strengthen grid resilience, ensuring a safer and more reliable power system in wildfire-prone regions.

System Hardening

Utilities operating in wildfire-prone regions face a growing challenge: the risk of power line-related ignitions and presence of flammable vegetation. While the probability of a fault occurring and igniting nearby fuel beds is relatively low, the consequences can be severe. Utilities must adopt a proactive, risk-reduction strategy focused on preventing faults and ignition sources before they lead to catastrophic wildfires. A strategic asset management approach plays a key role in preventing faults. By implementing system hardening — such as covered conductors, fire-resistant poles and undergrounding power lines — utilities can significantly reduce ignition risks.

While costly, undergrounding has been shown to reduce ignition risk by 99%, according to Pacific Gas and Electric Co. in its 2023-2025 Wildfire Mitigation Plan R5. Covered conductors provide a cost-effective alternative, reducing wildfire risk by up to 72%, as cited by Southern California Edison in its 2023-2025 Wildfire Mitigation Plan.

Vegetation Management

Beyond infrastructure, vegetation management is a crucial aspect of wildfire prevention. Overgrown vegetation near power lines remains a leading cause of utility-induced wildfires, making risk-informed vegetation management strategies essential. Traditional vegetation management follows a fixed schedule, but modern utilities are leveraging remote sensing, satellite imagery, light detection and ranging-based monitoring, and drone-based aerial imaging to optimize vegetation clearance schedules and identify high-risk areas. This data-driven approach improves efficiency, ensuring vegetation removal is targeted and effective in reducing ignition risks.

To further mitigate ignition risks, utilities need to address equipment vulnerabilities that contribute to fire hazards. Fire-prone components such as expulsion fuses and legacy surge arresters have historically been linked to ignition events. Replacing these with fire-safe alternatives has been shown to reduce ignition risk by more than 68%. Additionally, advanced fault detection systems, including high-speed protection relays and reclosers, help utilities to detect and isolate faults before they escalate into fire-starting events.

Advanced Protection

Protection strategies also play a crucial role in wildfire risk reduction. Utilities implement enhanced power line safety settings, including fast curve relays, sensitive ground fault (SGF) protection and fire-adaptive relay profiles. Disabling reclosers during high fire-risk periods prevents ignition from restrikes, reducing ignition risk by up to 40%. While reclosers improve reliability by restoring power after temporary faults, their operation during fire season poses ignition risks, leading to their disablement in high fire-threat districts (HFTDs).

Utilities can deploy wildfire tracking systems, which leverage fire sensors, drone-based infrared imaging and real-time weather analytics to detect fire activity early. Preemptive de-energization through public safety power shutoffs (PSPS) plays a key role in reducing wildfire risks in extreme weather conditions. While the impact of power outages on customers and critical facilities is a serious consideration, ensuring public safety should remain the top priority for utilities. In addition, utilities must be prepared to coordinate real-time wildfire suppression tactics with emergency responders. Fire suppression efforts can be enhanced through geospatial risk mapping, fire behavior simulations and predictive fire spread modeling. These tools provide actionable insights for prioritizing firefighting resources and ensuring grid operations remain adaptable to changing fire conditions.

Risk Mitigation Model

Electric utilities in wildfire-prone regions face growing threats of infrastructure-induced ignitions, leading to the implementation of comprehensive wildfire mitigation strategies. Utilities can follow a wildfire risk mitigation model to quantify both the likelihood of ignition events and their potential consequences.
Key inputs to assessing wildfire risk include weather conditions, historical wildfire records and the performance history of electric feeders, including past outage data, all of which contribute to estimating ignition probability. Historical outage and ignition data reveal recurring causes such as conductor clash, vegetation interference and aging infrastructure are major contributors to fire risk. Weather conditions further influence fire risk, with high winds and heat causing equipment failures, while drought conditions increase fuel availability. The utilities operating in wildfire-prone areas usually implement an ignition tracking system, combining geospatial incident records and meteorological data to develop predictive models.

A wildfire spread model can be used to evaluate the consequences of ignition. A fire behavior simulation tool models wildfire propagation and assesses potential impacts by simulating fire spread across specific landscapes. Then, the wildfire risk is determined by multiplying the probability of an ignition event, caused by a utility asset, by the resulting consequences. To improve fire modeling accuracy, weather scenarios are developed to represent conditions ranging from moderate to extreme. By simulating different scenarios, utilities can evaluate fire behavior under various environmental conditions and assess potential risks in the absence of intervention.

Wildfire risk assessment results can be visualized through heat maps, where darker shades indicate higher fire risk. These maps serve as decision-support tools for utilities, enabling them to prioritize mitigation efforts effectively.

Additionally, historical outage and ignition data are analyzed to pinpoint common ignition causes, such as conductor clash, equipment failure, vegetation interference and wire down. These causes are then mapped to wildfire mitigation strategies, including undergrounding, covered conductors, pole replacements and equipment upgrades. The effectiveness of each strategy can be continuously assessed to refine risk models and optimize prevention efforts.

Proactive Protocols

Utilities can take a proactive approach by implementing preemptive de-energization protocols based on a risk-prioritization system that integrates weather-level data (for example, wind, dead fuel moisture and precipitation) and feeder-level inputs (such as historical vegetation contact and vegetation management records). By using these combined inputs, the system can prioritize high-risk areas for intervention and recommend targeted preemptive measures, including de-energization in extreme fire conditions.
Also, to enhance situational awareness and response, utilities can invest in real-time weather stations and fire-detection cameras to monitor fire conditions dynamically. These systems allow for real-time adjustments in wildfire mitigation strategies.

The integration of multiple alerts from National Weather Service and Global Wildfire Information System can further guide risk-informed decision-making, ensuring more precise and proactive de-energization strategies.

A comprehensive communication plan also should be developed to support the preemptive de-energization protocol. This plan should incorporate stakeholder engagement, customer notifications, regulatory compliance measures, operational coordination and continuous improvement initiatives. By ensuring all regulatory bodies, emergency responders and affected customers are informed in advance, utilities can minimize the social and economic impact of de-energization while maintaining public safety.

In summary, a wildfire risk management strategy enables utilities to shift from a reactive to a proactive approach by integrating advanced technology, predictive modeling, data-driven decision-making and adaptive infrastructure planning. Implementing these mitigation strategies enhances a utility’s ability to prevent, mitigate and recover from wildfires, ultimately protecting critical infrastructure and the community it serves. 

About the Author

Alireza Majzoobi

Dr. Alireza Majzoobi, Ph.D., PE, has 15 years of experience in power system operations, smart grid software solutions and data analytics. He is currently an advisor at Quanta Technology LLC, working within the asset management team with a focus on grid resilience and wildfire risk management for various electric utilities.

About the Author

Zhenzhen Zhang

Dr. Zhenzhen Zhang, Ph.D., specializes in climate risk, geospatial modeling and machine learning for utility asset management. She applies advanced data analytics to support wildfire risk assessment, vegetation management and infrastructure resilience planning.

About the Author

Daniel Haughton

Daniel Haughton, Ph.D., is T&D Planning Director at LUMA Energy. He was also a director of T&D Engineering Support at Arizona Public Service (APS) for 11 years. He has done work on renewable integration, power grid modernization and reliability improvement for Quanta Services and taught power systems analysis and protection concepts at Arizona State University, where he also received his Ph.D. in Electrical Engineering.

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