According to the drawbacks of the unchanged swim step and slow velocity in the bacterial foraging algorithm,a bacterial foraging optimization algorithm based on immune algorithm (IBFO) was introduced in reactive power optimization.The IBFO gives bacteria the ability of context-aware,and increases the convergence speed by using the sensitivity to adjust the group swim step.The idea of clonal selection in immune algorithm was introduced in bacterial foraging,and the bacterial cloning,high-frequency variation and random crossover of the elite group were achieved so as to increase the accuracy of convergence.The IBFO was implemented on the IEEE 14 bus and IEEE 30 bus system.The results show that the new algorithm has stronger global optimal searching ability,faster convergence rate and better robustness compared with other optimization algorithms.Therefore,as a new approach,it can solve the problem of reactive power optimization in power systems.