Wildfires can be a source of vulnerability for power systems operations.
These events can especially affect the operation of distribution systems. They
can interrupt energy supply, increase costs, and decrease grid resilience. Numerous approaches can be executed to prevent them. In this dissertation, it
is considered the relationship between operative actions and the probability
of wildfire disruption. This type of study has not been properly evaluated in
technical and scientific literature. By not recognizing this aspect, the operation
of power systems may be impaired. Properly modeling this dependency could
lower wildfire disruption and loss of load. Considering this, a two-stage distributionally robust optimization problem with decision-dependent uncertainty
is developed to consider distribution system multiperiod operation. The first
stage determines the optimal switching actions and line investments, and the
second stage evaluates the worst-case expected operation cost. It is designed
a decision-dependent uncertainty framework where the line failure probabilities are a function (dependent) of its power flow levels. An iterative method
is proposed to solve this model and an out-of-sample analysis is developed to
validate it through different case studies. Results showed that, by neglecting
the uncertainty dependency on operative decisions, there could be a higher
expected loss of load and a higher operational cost. By considering this new
approach when operating power lines, the grid s resilience could be improved
and wildfire consequences can be mitigated with less costly actions.
|