.png){kind=icon}
.png){kind=icon}
Return
Decision-Dependent Resilience Enhancement Strategy for Distribution Systems Against Endogenous Wildfires
.png){kind=icon}
PRE
AI
C
S
Y
Y
DOI：10.1109/TSG.2026.3650758.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The increasing frequency and severity of wildfires pose significant threats to utility infrastructure and community safety. Wildfires can be ignited due to component failures under extreme weather conditions. System hardening measures aimed at preventing these failures can reduce the probability of endogenous wildfire ignition, introducing decision-dependent uncertainty (DDU). However, existing methods that consider such DDU typically assume independent component failures, neglecting the critical interdependencies between components destroyed by wildfire and those affected by their spread. These interdependencies render such methods inadequate. To address this, we propose a novel formulation that incorporates both wildfire-ignition DDU and a second type of DDU - the interdependency between wildfire-ignited and wildfire-affected components. We develop a two-stage wildfire-preventive decision-dependent resilience enhancement (WDDRE) model for distribution systems. The model optimizes line hardening, distributed generation allocation, and network reconfiguration to enhance system resilience by preventing endogenous wildfire ignition caused by component failures. Numerical experiments demonstrate the effectiveness and superiority of the WDDRE model, showcasing its robustness in managing wildfire stochasticity and the two kinds of DDUs related to planning decisions, significantly reducing potential wildfire risks.
Keywords:
Wildfires
Ignition
Resilience
Planning
Uncertainty
Load modeling
Resource management
Reactive power
Robustness
Prevention and mitigation
Decision-dependent uncertainty
resilience enhancement
wildfire
distribution system
stochastic optimization
Journal
IF:
9.8
Papers:
5.6K
Citations:
4.3W
Organization
Cited Papers