CAJ | 학술논문

建立了无功优化的数学模型，针对粒子群算法易陷入局部最优解、收敛精度差的缺点，将改进粒子群优化算法应用到电力系统无功优化中。对粒子群的速度公式进行了改进，并在算法中引入反正切惯性权重和阈值来增强搜索全局最优解的能力。通过对IEEE30节点的算例仿真，证明改进后的粒子群算法在电力系统无功优化问题上具有一定的可行性。与PSO的结果对比表明该算法在一定程度上提高了计算的精度。
건립료무공우화적수학모형，침대입자군산법역함입국부최우해、수렴정도차적결점，장개진입자군우화산법응용도전력계통무공우화중。대입자군적속도공식진행료개진，병재산법중인입반정절관성권중화역치래증강수색전국최우해적능력。통과대IEEE30절점적산례방진，증명개진후적입자군산법재전력계통무공우화문제상구유일정적가행성。여PSO적결과대비표명해산법재일정정도상제고료계산적정도。
This paper established a mathematical model of reactive power optimization .In view of the shortcomings of standard PSO that local optimum and poor convergence precision , this paper introduced an improved particle swarm optimization algorithm to the reactive power optimization of power system .The paper improved the speed formula of PSO and introduced arctangent inertia weight and threshold to enhance the ability to find the global optimal solution . Simulation results of IEEE 30-bus system show that the improved particle swarm algorithm for reactive power optimiza-tion problem is feasible .Comparing with the results of PSO , we can find that improved particle swarm optimization al-gorithm improve the calculation accuracy in a certain extent .