Event-driven frequency and voltage stability predictive assessment and unified load shedding

A well-designed scheme is essential for assessment and protection of the stability of power system after an unanticipated event. This paper proposes a strategy for regulating three-phase faults and other events that endanger frequency or voltage stability of the system. The aim is to promptly identify such events utilizing supervised learning-based classification modules, and initiate suitable emergency control. The imbalances of active and reactive power after an event have been utilized to predict the stability of system. A new optimization-based formulation has been presented for estimation of reactive power imbalance. An event predicted as unstable is counteracted by prompt load shedding. Conventionally, load shedding is based on frequency or voltage information independently which reduces the effect of load shedding. This work proposes a new load shedding procedure considering both active and reactive power. The proposed scheme is tested on New England (NE) 39-bus system and Northern Regional Power Grid (NRPG) 246-bus system, and results of load shedding have been compared with two existing load shedding schemes. The results indicate the accuracy of classification modules in identifying faults and unstable events, and the proposed load shedding restores stability of the system with less amount of load shed and better voltage profile.