A probabilistic indicator of the optimal operator action time under short-time emergency line loadings

This paper introduces the concept of a probabilistic indicator to aid power system operator decision making during short-time emergency loadings stemming from operational uncertainty. It is based on a state based Monte Carlo sampling method and is thus able to capture the stochastic nature of power system operation. The methodology developed within this paper also incorporates conductor properties and operation by integrating dynamic thermal rating (DTR) data on the premise that DTR will be a key component of the smart grid in enabling smarter rating of power lines. The DTR weather is modeled as a Markovian process to account for the transitions between weather states. This methodology is tested and validated on the 24 bus IEEE-RTS in order to demonstrate the indicator's ability to evaluate areas of risk as well as opportunity in regard to the increase of overloading durations for a given maximum operating temperature and system operation state.