Abstract:

Power system reactive power optimization is an important link in improving the power quality and ensuring the power grid to operate.This paper establishes a reactive power optimization model of considering minimization of loss and voltage deviation and maximum of voltage stability margin.The adaptive mutation particle swarm optimization is introduced for the threeobjective reactive power optimization.This algorithm monitors particle group status of gathering dynamically by group fitness variance and adopts the method of adding random disturbance to vary gathered particles,using weight of inertia adaptive adjustment to jump out of local optimal and prevent premature,thus higher convergence speed and accuracy.The algorithm is implemented on the IEEE14 bus system.Comparison with other algorithms shows the superiority and practicability of this model and algorithm in solving multiobjective power system reactive power optimization problems.

Key words: particle swarm optimization;mutation;threeobjective;reactive power optimization;variance