The proposed resilient operation approach can be adapted to address other extreme weather events, such as hurricanes and ice storms, by modifying the risk assessment and optimization framework to incorporate the specific characteristics and impacts of these events.
Risk Assessment: Similar to the wildfire ignition risk score, a risk quantification model can be developed for hurricanes and ice storms. This would involve analyzing historical data to identify the likelihood of such events and their potential impact on power lines and infrastructure. For hurricanes, factors such as wind speed, storm surge, and flooding should be considered, while for ice storms, the weight of ice accumulation on power lines and the resulting mechanical stress should be evaluated.
Operational Constraints: The optimization model can be adjusted to include new operational constraints that reflect the unique challenges posed by hurricanes and ice storms. For instance, during a hurricane, the model could prioritize the de-energization of lines in high-risk areas to prevent damage, while ensuring that critical infrastructure remains powered. In the case of ice storms, the model could account for the increased risk of line failure due to ice loading.
Multi-Hazard Framework: A multi-hazard optimization framework can be developed that simultaneously considers the risks from wildfires, hurricanes, and ice storms. This would involve creating a comprehensive risk profile for each line and bus in the power system, allowing operators to make informed decisions based on the most pressing threats at any given time.
Dynamic Risk Tolerance: The risk tolerance level can be made dynamic, allowing system operators to adjust their risk appetite based on the forecasted severity of the weather event. For example, during a hurricane warning, operators might adopt a more conservative approach, while during a less severe weather forecast, they could afford to take on more risk.
Integration of Real-Time Data: Incorporating real-time weather data and predictive analytics into the optimization model can enhance its responsiveness to changing conditions. This would allow for real-time adjustments to the energization status of lines based on the evolving risk landscape.
By extending the resilient operation approach in these ways, the power system can be better equipped to handle a variety of extreme weather events, ensuring reliability and safety for customers.