For 24 hours reactive power optimization in the power system, the optimization method is using particle swarm optimization algorithm and penalty function method to bring all the inequality constraint equations into the original objective function, which is optimized as a penalty term; and the optimization goal is the minimum economic cost of the objective function throughout the day; the optimization procedure is composed of two stages of static and compositive optimization. Based on the on-online forecasted load powers, the shunt capacitors switching states and transform tap stalls for 24 hours are determined. The particle swarm algorithm is used to solve the multi-objective reactive power optimization problem, which can not only reduce the active power loss effectively and the cost of reactive power compensation, but also improve the convergence performance, the convergence speed and the stability.