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Cascading failure causes a major risk to society currently. To effectivelymitigate the risk, dynamic thermal rating (DTR) technique can be applied as acost-effective strategy to exploit potential transmission capability. From theperspectives of service life and Braess paradox, it is important andchallenging to jointly optimize the DTR placement and operation schedule forchanging system state, which is a two-stage combinatorial problem with onlydiscrete variables, suffering from no approximation guarantee and dimensioncurse only based on traditional models. Thus, the present work proposes a noveltwo-stage submodular optimization (TSSO) of DTR for risk mitigation consideringplacement and operation schedule. Specifically, it optimizes DTR placement withproper redundancy in first stage, and then determines the corresponding DTRoperation for each system state in second stage. Under the condition of theMarkov and submodular features in sub-function of risk mitigation, thesubmodularity of total objective function of TSSO can be proven for the firsttime. Based on this, a state-of-the-art efficient solving algorithm isdeveloped that can provide a better approximation guarantee than previousstudies by coordinating the separate curvature and error form. The performanceof the proposed algorithms is verified by case results.

Two-Stage Submodular Optimization of Dynamic Thermal Rating for Risk Mitigation Considering Placement and Operation Schedule