电力系统实时运行状态的估计和预报

Estimation and Forecasting of Real-Time Power System Operation States

本文用自适应预报方法设计了动态估计器,对电力系统实时运行状态进行估计和预报,并应用稀疏矩阵技术和迭代Kalman滤波方法实现动态状态估计算法,在几个系统上验证了该算法的正确性和有效性。

In this paper, an adaptive forecasting method is described and used to build up power system model for the estimation and forecasting of real-time power system operation states. Sparse matrix technique and iterative Kaiman Filtering method are used to implement the estimation and the forecasting. Digital tests on several power systems show that the method proposed in this paper is valid and efficient.