Reactive power optimization of the power system is an effective way to keep the power system safe and economical. The main purpose of reactive power optimization is that it can improve the voltage quality and reduce the active power loss of the power system. The reactive power optimization problem of the power system is a complex and nonlinear problem and it should adjust the variables including control variables and state variables. This paper establishes a differential evolution flower pollination algorithm based on particle swarm optimization (DFPA-PSO) in view of the shortcomings of the accuracy of the traditional particle swarm optimization algorithm. The DFPA-PSO combines global search, local search and mutation operations with the flower pollination algorithm. Not only can it widen the search space of particles, but also it increases the diversity of the particles. The DFPA-PSO is applied to the IEEE-14 bus system, which takes into account of loss minimization, voltage level best target and maximum static voltage stability margin. Compared with other algorithms, the results show that DFPA-PSO has stronger global searching ability, faster convergence rate, better robustness and the active power loss is also reduced, thus proving the superiority of DFPA-PSO.

The voltage level to reactive power optimization dispatch and control problem is incorporated． A model of reactive power optimization
is established based on multi-objective differential evolution，which takes into account of loss minimization，voltage level best
target． Considering the drawbacks of traditional differential evolution ( DE) algorithm such as premature and slow search speed，a
strategy of self-adapting parameter improved differential evolution algorithm was proposed and first applied in reactive power optimization
problem． By adjusting the mutation F and crossover CR during the evolution process，the diversity of population is increased and the
global search area is expanded，which avoids algorithm into a local optimal solution，at the same time，the convergence speed is accelerated
later． The simulations are carried out on IEEE-14 bus system，and the results show the validity of the proposed algorithm．