Dynamic Thermal Rating for Efficient Management of Post-Contingency Congestions

This paper presents a novel optimal power flow (OPF) based approach for post-contingency management of severe congestions, aimed at maximizing lead time available to the network operators before the next contingency occurs. The approach first computes the maximum allowed overloading times for the congested transmission lines and transformers, using their dynamic thermal models. Afterwards, the OPF analysis is performed to identify the maximum lead time available to the network operator for managing post-contingency constraints and for devising and implementing the most efficient corrective actions. The corresponding OPF problem is modelled as a mixed-integer nonlinear optimization problem and solved using mixed-discrete particle swarm optimization (MDPSO) approach. The approach is illustrated on a modified IEEE 14-bus network and obtained results demonstrate that presented approach can manage considered constraints within the available lead time.