改进粒子群算法在电网无功优化中的应用

Application of improved particle swarm optimization in power system reactive power control

粒子群算法作为一种随机搜索算法,适合解决电网无功优化问题。考虑到粒子群算法收敛速度过快,容易进入局部收敛,导致收敛精度不高,研究了粒子群算法的改进措施。建立了一个全面考虑实际约束条件和无功调节手段的无功优化数学模型,提出了采用改进粒子群算法求解电网无功优化问题的方法,以确定无功优化的最优方案。以IEEE14节点系统进行仿真分析,对3种不同方案进行了对比,结果表明所用方法寻优质量高,不仅节点电压满足系统运行要求,而且系统网损也有一定程度的降低,采用该改进粒子群算法进行电网无功优化行之有效。

Particle swarm optimization （PSO） is a random search algorithm which is suitable for solving reactive power optimization problems. Because the algorithm is prone to trap in the local minimum point with low convergence accuracy, improvement measures are studied. A reactive power optimization model considering both practical constraints and reactive regulation methods is established. The method based on improved PSO for reactive power optimization is then proposed. Comparison of simulation results on the IEEE 14 bus system with three different schemes proves effectiveness of proposed algorithm. It is able to not only satisfy the bus voltage requirement, but also reduce the system loss while optimizing reactive power in the system.