Multi-objective optimal preventive islanding based on stochastic backward elimination strategy considering uncertainties of loads and wind farms

摘要

Nowadays, occurrence of severe contingencies may cause an interconnected power system to lose stability and lead to the partial or wide-spread cascading failures. Hence, intentional islanding is the last countermeasure to mitigate the system vulnerability and avoid the catastrophic wide area blackout. This paper proposes a novel probabilistic splitting strategy for generating all possible islanding solutions and evaluating different static and dynamic constraints in reduced power system graph. The proposed stochastic scenario generation algorithm investigates the steady-state stability of all partitions in each generated solution taking into account the uncertainties of loads and wind farms. Multiobjective binary imperialistic competitive algorithm is then developed to find the optimum line switching points that minimizes load-generation mismatch and probability of islands' partial blackout, maximizes voltage stability security margin, and satisfies the slow coherency, connectivity, voltage, and the transmission capacity constraints. Monte Carlo simulation and point estimation method are applied in the stochastic programming model to investigate the islands' stability, calculate the optimization error, and determine the critical stressed transmission lines and PQ-busses under uncertain operating condition. The validity and speed of the proposed approach are revealed using simulation on IEEE 39-bus standard system.