Global optimization techniques such as genetic algorithm (GA), simulated annealing (SA) and tabu search (TS) are widely used to combinatorial optimization in recent years. Combining the advantages of individual algorithms, three GA/SA/TS combined algorithms for the reactive power optimization are proposed in this paper. Trying to reasonably combine local and global search, they adopt the acceptance probability of SA to improve the convergence of the simple GA, and apply TS to find more accurate solutions. Results of a practical area power system in Shandong province of China demonstrate that the proposed method is effective to find better solutions within reasonable time.