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

Cascading failure causes a major risk to society currently. And dynamic thermal rating (DTR) technique is cost-effective approach mitigate the by exploiting potential transmission capability. From perspectives of service life and Braess paradox, it important challenging jointly optimize DTR placement its operation schedule for changing system state, which two-stage combinatorial problem with only discrete variables, suffering from no approximation guarantee dimension curse in traditional solving algorithms. Thus, present work proposes novel submodular optimization (TSSO) mitigation considering schedule. Specifically, optimizes proper redundancy first stage, then determines corresponding each state second stage. Under condition Markov features sub-function mitigation, submodularity total objective function TSSO can be proven time. Based on this, state-of-the-art efficient algorithm developed that provide better than previous studies coordinating separate curvature error form. The performance proposed model verified case results.