改进粒子群算法在无功优化中的应用

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。

Application of Improved Particle Swarm Optimizationin Reactive Power Optimization of Power System

This paper established a mathematical model of reactive power optimization. For the shortcomings of standard PSO that easily falling into local minima and poor convergence precision, this paper apply an improved particle swarm optimization algorithm to the power system reactive power optimization. The paper improved the formula of speed 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 improve particle swarm algorithm for reactive power optimization problem is feasible. Comparing with the results of PSO, we can find that improved particle swarm optimization algorithm improve the calculation accuracy in a certain extent.