基于PMU的分布式电力系统动态状态估计新算法

New Distributed Power System Dynamic State Estimation Algorithm Based on PMU

随着电力系统的发展,区域电网互联,形成更大的系统。各区域电网相对独立,且有各自相对独立的调度中心。为适应这种分区管理模式,状态估计应采用分布式并行算法。在动态估计扩展Kalman滤波算法的基础上,结合搭接式分布并行算法,提出了一种基于相量测量单元(PMU)的分布式电力系统动态状态估计新算法。该算法利用少量PMU测点,真正实现各子系统的并行计算,避免了原算法进行串行等待的过程。并结合量测数据预处理、对雅可比矩阵加权等方法,加快了计算速度,提高了数值精度和稳定性。最后给出了IEEE 14节点的仿真结果,验证了该算法的有效性及优越性。

With the development of power system, power networks become very large through interconnected local networks. Each area has relatively independent dispatching system, so the distributed dynamic state estimation algorithm is used to accommodate to this pattern. In the paper, based on the extended Kalman filtering techniques and pervious distributed algorithm, a new distributed power system dynamic state estimation algorithm based on PMU is presented. By using the data of PMUs, parallel process is really achieved, and the relay is avoided by exchanging data of the previous one. Combined with the methods of processing the data before filtering step, weighing the elements of Jacobian matrix and so on, the computational speed is fast and the result is accurate. The results of an IEEE-14 test system demonstrates its advantage.