It is of great significance for the reactive power optimization algorithm to improve the security and stability of the power system. To avoid the disadvantages of the traditional particle swarm optimization algorithm

prematurity and local convergence

while optimizing large-scale

strong nonlinear reactive power

the logistic chaotic map

for its advanced searching ability

was applied in the optimization variable process of this algorithm. Besides

a chaotic sequence combining Chebyshev chaotic map with logistic chaotic map was applied to obtain a uniform initial value so as to improve the global optimization ability of the algorithm. As to the problem of inertia weight

the algorithm gave a dynamic inertia weight

based on population velocity. The results show that it performs better in global searching ability and efficiency.