In the past decades, wildfire hazards occurred more and more frequently. During summer seasons in regions with high temperature, power distribution systems especially those located near the forests are prone to wildfires. The temperature of conductor lines exposed to the fire increases rapidly, the shape and strength of which are, therefore, permanently reduced. The conventional reliability view is insufficient to cope with these challenges in modern power systems since such hazards cause prolonged and extensive outages, much more severe than those previously accounted for in system reliability assessments. Improving the resilience of the power grid, hence, becomes increasingly important and urgent. To enhance the resilience of the system against wildfires, the characteristics of wildfires need to be first studied so that effective mitigation strategies, e.g., dynamic line rating of the overhead power lines, can be proposed taking into account the impact of fires and the existence of uncertainties.

This thesis mainly focuses on designing an optimal operation strategy to minimize load shedding when distribution lines are affected by wildfires. Taking the uncertainties related to solar and wind—that influence the spread of wildfire and the renewable generators—into account, a stochastic mixed-integer nonlinear programming model is proposed and applied to a modified 33-bus power distribution system. The formulation aims to minimize the social cost which associates with the status of each wind turbine and the energy storage systems. By this means, the most effective operation strategy against wildfires is found, thereby enhancing the grid resilience and reducing the load outages during and following wildfire event. A sensitivity analysis is conducted on the overhead lines affected and the number of active components in the system to further investigate the best mitigation approach in the power distribution system when exposed to massive wildfires.