基于局部信息融合和估计投影法的多区域电力系统状态估计

Multi-Area Power System State Estimation Based on Partial Information Fusion and Estimate Projection

在多区域互联电力系统中,由于状态变量维数高和大量量测数据处理等问题,集中式估计的实现变得困难。提出一种基于局部信息融合和估计投影法的多区域电力系统状态估计新算法。首先,各区域独立运行加权最小二乘迭代得到本地估计值,并将协调中心边界状态估计值及对应的协方差子矩阵发送至协调中心;得到各区域边界信息后,协调中心采用最小二乘信息融合算法对系统边界状态作协调估计,并返回边界协调估计值至各区域;最后,根据边界协调估计值,各区域通过估计投影法对其内部状态作修正。该方法适应于全系统有/无相量测量单元(PMU)的情况,且所需通信量少,易于实现。算例仿真结果表明,所提算法具有良好的估计精度和实时性。

In multi-area interconnected power systems, the centralized estimation is difficult to implement because of the high state variable dimension and the large measurement data processing. This paper proposes a new algorithm of multi-area power system state estimation based on partial information fusion and estimate projection. In the proposed algorithm, each subarea individually obtains local estimates by implementing weighted least square iteration, and sends the local estimates of the boundary bus states to the coordination center. The coordination center applies least square fusion algorithm to calculate the coordinated estimates of total boundary bus states. According to the coordinated estimates of the boundary bus states, each subarea can further correct the local estimates of the internal states. The proposed algorithm can be implemented in the power system with PMU or without PMU. Moreover, the proposed algorithm only needs very few communication data, which also can be easy to implement. The test simulation results have proved that the proposed algorithm has good estimation accuracy and real-time property.