Keywords
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Monte Carlo simulation (MCS), multi‐objective binary imperialistic competitive algorithm, point
estimation method (PEM), static voltage stability security margin, stochastic backward elimination
method
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Abstract
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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. Multi‐
objective 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.
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