论文标题
部分可观测时空混沌系统的无模型预测
Dynamic Response Recovery Using Ambient Synchrophasor Data: A Synthetic Texas Interconnection Case Study
论文作者
论文摘要
大区域动态研究对于确保电网的稳定性和可靠性至关重要。本文提出了一个全面的框架，用于使用普通网格操作期间收集的无处不在的快速速率环境数据来推断小信号制度中的动态响应。我们已经表明，通过仅在这两个位置收集的交叉相关角度和功率流数据流，只要基于频率数据就超越了以前的工作，就可以以无模型的方式恢复任何一对位置之间的冲动响应。结果是通过基于模型的二阶旋转动力学的基于模型的分析来确定的。数值验证证明了其适用于现实的电力系统模型，包括非线性，高阶动力学。特别是，使用合成Texas互连（TI）系统的合成PMU数据的案例研究强烈证实了使用角度PMU数据比频率数据进行现实世界动力系统动态建模的好处。
Wide-area dynamic studies are of paramount importance to ensure the stability and reliability of power grids. This paper puts forth a comprehensive framework for inferring the dynamic responses in the small-signal regime using ubiquitous fast-rate ambient data collected during normal grid operations. We have shown that the impulse response between any pair of locations can be recovered in a model-free fashion by cross-correlating angle and power flow data streams collected only at these two locations, going beyond previous work based on frequency data only. The result has been established via model-based analysis of linearized second-order swing dynamics under certain conditions. Numerical validations demonstrate its applicability to realistic power system models including nonlinear, higher-order dynamics. In particular, the case study using synthetic PMU data on a synthetic Texas Interconnection (TI) system strongly corroborates the benefit of using angle PMU data over frequency data for real-world power system dynamic modeling.
