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Probabilistic load flow (PLF) is an efficient tool to assess the performance of a power network considering random variables. In this paper, an improved Latin hypercube sampling (LHS) is proposed to solve PLF considering correlated input random variables. The permutation of samples in LHS is treated as a combinatorial optimization problem and handled by a designed genetic algorithm combined with local...
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