基于PSO算法的电力系统优化研究

针对电力系统的无功功率优化问题,构建了多约束条件的目标函数。在电力系统的建模过程中,设定了电力系统的结构参数和负荷参数,并将设置负荷节点之间的电压越界参数、发电机无功越界参数设置为惩罚处置项;在PSO算法的设计中,设置了粒子状态、适应度函数以及惩罚权重参数。以具体结构的电力系统无功功率优化为实验对象,分别采用数学规划法、遗传算法和PSO算法进行优化。优化结果显示,PSO算法更能有效地降低电力系统的功率损耗,同时其收敛速度也最为理想。

Research on power system optimization based on PSO algorithm

In terms of the reactive power optimization in power system, an objective function with multiple constraints is constructed. In power system modeling, the structure parameters and the load parameters of power system are set up. The voltage transboundary parameter and the reactive power transboundary parameter between the load nodes were set as the penalty disposal items. In the design of PSO algorithm, particle state, fitness function and penalty weight parameters are set up. Taking a power system as experimental object, reactive power is optimized respectively by mathematical programming method, genetic algorithm and PSO algorithm. The results show that PSO algorithm can most effectively reduce the power loss, and the convergence speed is the best.