基于量子粒子群算法多目标优化的配电网动态重构

Multi-objective optimization of distribution network dynamic reconfiguration based on integer coded quantum particle swarm optimization algorithm

为保证配电网动态重构后系统安全稳定的运行,提出了以网损和节点电压稳定性为目标函数的量子粒子群算法的配电网动态重构。针对配电网动态重构过程中时段划分问题,提出以负荷曲线的单调性和幅值变化大小为依据初步划分时间段落。采用整数型量子粒子群算法进行动态重构,重构过程中以相邻时段的网损变化值的关系获取最佳重构段落,然后综合考虑配电网网损最小和节点电压值最大且波动最小为目标寻找最佳重构结构。以IEEE33配电系统为例验证了所提方法的有效性和实用性。

To ensure the dynamic reconfiguration of distribution network system safe and stable operation, a dynamic reconfiguration method for distribution network is proposed based on integer coded quantum particle swarm optimization algorithm which takes the minimum network loss and node voltage stability as the objective function. First, a day of load forecasting curve is divided into several time intervals based on its monotonicity and amplitude changes. Then integer quantum particle swarm optimization algorithm is adopted to realize dynamic distribution network reconfiguration. In order to find the best number of refactoring, the optimal time refactoring function is proposed based on adjacent time refactoring changes value network loss. In consideration of the power distribution network loss minimum and node voltage fluctuations largest and smallest for the target, we are looking for best reconstruction of the distribution network structure on the basis of IEEE33 distribution system, the reconstructed results verify the validity of the proposed method.