基于混合量测的电力系统状态估计混合算法

研究了相量量测装置(PMU)相量量测和监控与数据采集(SCADA)量测混合使用时的数据匹配问题,提出了利用状态量转换预测得到预报系统状态和预报节点注入电流向量的方法。在此基础上,提出了应用PMU实时相量量测和预报节点注入电流向量的线性静态状态估计算法,以及应用PMU实时相量量测和预报系统状态的线性动态状态估计算法。文中将这2种算法与传统状态估计算法相结合,组成了状态估计混合算法,保证了状态估计的计算精度。该混合算法有效减少了状态估计的计算时间,对PMU的量测配置也没有严格的要求,具有很好的通用性。最后采用IEEE30节点系统对该方法进行了验证。

A Hybrid Algorithm for Power System State Estimation Based on PMU Measurement and SCADA Measurement

The data matching problem in aligning the phasor measurement unit (PMU) measurement and SCADA measurement is studied. The state conversion forecast is used to get the forecast state and node injection current vector. A linear static state estimation algorithm using PMU real-time measurement and forecast node injection current vector, and a linear dynamic state estimation algorithm using PMU real-time measurement and forecast state are proposed. By combining the two algorithms and traditional state estimation, a hybrid algorithm suitable for any PMU placement status is formed. The linear state estimation algorithm is used to reduce the calculating time and traditional state estimation algorithm to ensure calculating accuracy. The effectiveness of the algorithm proposed is illustrated with numerical simulation using the IEEE 30-bus system.