The value of real-time adjustable remedial action schemes

Abstract

Remedial action schemes (RAS) are often seen as an inexpensive way to relieve contingency-related grid congestion without building new transmission infrastructure. However, RAS settings often remain fixed during real-time operation and do not adapt to variation in operating conditions due to renewable and distributed generation. This lack of adaptability may cause suboptimal settings and possibly insecure operations. To assess the value of allowing RAS settings to vary real time and the benefit of considering multiple load and generation scenarios, we propose a mixed integer optimization framework which identifies optimal RAS actions while incorporating multiple load and renewable energy scenarios. We also propose an iterative algorithm that efficiently solves the optimization problem, leveraging the fact that only a few scenarios and contingencies are binding at optimality. We demonstrate the benefits of (i) updating RAS more frequently and (ii) considering multiple load scenarios by performing case studies on the RTS-GMLC system.