发电机运动轨迹预测理论的研究

Study on prediction of generator trajectory

广域测量系统的发展,为根据实测电力系统轨迹进行暂态不稳定性的紧急控制提供了可能。利用实时数据进行超实时预测能尽早投入控制措施,阻止失步的发生。因此,研究高精度长时间的轨迹预测具有重要意义。从发电机运动方程出发,导出了适用于电力系统的滚动自记忆预测方法。该方法先用三角函数拟合不平衡功率,然后由不平衡功率预测角速度,最后由自记忆公式预测功角。IEEE9节点系统的仿真计算结果表明,该方法可以很准确地预测未来至少0.5 s的功角轨迹,同三角函数、自回归预测相比,具有预测精度高、预测时间长的优点。

With the development of wide area measurement system, it is possible for power system transient instability control based on real-time trajectory. Using real-time data to predict can take control measures as soon as possible, which can prevent out of step. Therefore, it is very important to study high-precision and long-time trajectory prediction. Proceeding from motion equations of generator, a rolling self-memory prediction method for power system is deduced. First, trigonometric function is used to fit unbalanced power; then, angular velocity is predicted by unbalanced power; at last, according to the self-memory prediction formula, power angle can be obtained. The simulation result of IEEE9 system shows that, the method mentioned in this paper can accurately predict at least 0.5s＇ future trajectory. Compared with trigonometric function prediction and autoregressive prediction, this method can predict in a longer time with a higher accuracy.