Abstract
SUMMARY This study proposes a new strategy to solve the problem of radial power distribution system (RDS) reconfiguration in a multi-objective and constrained environment. Due to the presence of various conflicting objectives and constraints, the proposed strategy uses the Elitist Non-Dominated Sorting Genetic Algorithm-II (NSGA-II), an effective evolutionary multi-objective optimization technique. NSGA-II determines a set of pareto-optimal solutions for the power distribution system topology, considering power losses, reliability and investment in tie-switches. The methodology adopted to evaluate the RDS reliability uses a non-sequential Monte Carlo Simulation and is focused on the impacts of branch failures for interruption energy assessment. The effectiveness of the proposed methodology is demonstrated on a 69 bus RDS. Copyright © 2013 John Wiley & Sons, Ltd.
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