  Ice storms, known for their severity and predictability, necessitate
proactive resilience enhancement in power systems. Traditional approaches often
overlook the endogenous uncertainties inherent in human decisions and
underutilize predictive information like forecast accuracy and preparation
time. To bridge these gaps, we proposed a two-stage risk-informed
decision-dependent resilience planning (RIDDRP) for transmission systems
against ice storms. The model leverages predictive information to optimize
resource allocation, considering decision-dependent line failure uncertainties
introduced by planning decisions and exogenous ice storm-related uncertainties.
We adopt a dual-objective approach to balance economic efficiency and system
resilience across both normal and emergent conditions. The first stage of the
RDDIP model makes line hardening decisions, as well as the optimal sitting and
sizing of energy storage. The second stage evaluates the risk-informed
operation costs, considering both pre-event preparation and emergency
operations. Case studies demonstrate the model's ability to leverage predictive
information, leading to more judicious investment decisions and optimized
utilization of dispatchable resources. We also quantified the impact of
different properties of predictive information on resilience enhancement. The
RIDDRP model provides grid operators and planners valuable insights for making
risk-informed infrastructure investments and operational strategy decisions,
thereby improving preparedness and response to future extreme weather events.
