基于机端PMU量测的系统受扰轨迹预测

提出了基于机端相量测量单元量测数据的多机系统受扰轨迹预测方法，结合状态估计或潮流数据，在系统受扰后将其降阶简化为仅含有配置了相量测量单元的发电机节点系统，利用相量测量单元的量测数据修正降阶系统节点电压和电流之间的关系，然后将其代入相应的发电机模型，从而实现了系统受扰轨迹预测。该方法采用时间间隔较大的状态估计或潮流数据计算节点电压和电流传递关系矩阵的初值，并利用该矩阵主对角元的变化反映受扰后系统各元件的详细模型、网络拓扑和参数的改变，然后使用相量测量单元毫秒级的量测数据对其进行修正，从而为在实际应用中将相量测量单元与SCADA系统相结合做出了有益探索。最后以一个6机25节点系统为例验证了该方法的有效性。

Perturbed Trajectory Prediction Based on PMU Measurement in Power Plants

A method to predict the perturbed trajectories of multi-machine power system based on measurement results of PMU (phasor measurement unit) equipped at generator terminals is proposed. Combined with state estimation or power flow data, the power system is order-reduced and simplified to such a system consisting of the generator nodes equipped with PMU; after the power system is perturbed, utilizing the measured data of PMU the relations between voltages and currents of the order-reduced nodes is modified and substituted into corresponding generator models to realize the perturbed trajectory prediction of the power system. In the proposed method the data from state estimation or power flows during larger time interval is used to calculate nodal voltages and the initial value of current transitive-relationship matrix; the variation of diagonal elements of this matrix reflects the variations of the detailed models of system components, network topology and parameters after the perturbation, then by use of the PMU measured data in millisecond level the primary diagonal element can be modified. Finally, the simulation of a 6-machine 25-bus power system validates the effectiveness of the proposed method.