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Conventional differential evolution (CDE) algorithm runs the risk of being trapped by local optima because of its greedy updating strategy and intrinsic differential property. A novel simulated annealing differential evolution (SADE) algorithm is proposed to compute optimal reactive power flow (ORPF). With the aid of simulated annealing updating strategy, SADE is able to escape from the local optima, and achieve the balance between exploration and exploitation. Optimization results on ORPF of IEEE standard 118 nodes system indicate that SADE outperforms CDE in the global search ability.