High-resolution empirical mapping methods of dynamic oscillation responses for large power systems have recently been considered to treat the data gaps and its space-time compensation. Although virtually-designed data of signals are not a real condition for monitoring systems, these can be implemented to study objectively the moving features and dominant paths of inter-area oscillation modes. This paper demonstrates the application of the space-time interpolation of wide-area measurements to compensate data gaps and degraded space-time resolution for modal decomposition. Contributions of empirical mode coherence for splitting and clustering data in density factors are also presented to the classification area. The method involves the space-time high-resolution interpolation of empirical mode components for splitting closely-related oscillation modes at intrinsic timescales, preserving their multivariate waveform features. Therefore, high-resolution empirical viewing maps of remotely-sensed dynamic responses, with degraded space-time resolutions, are derived to study the observance and dominant paths of wide-area oscillation modes. The proposed approach is numerically applied to the IEEE 16-generator 68-bus test system for efficiently defining empirical viewing maps of inter-area oscillation modes.

大电力系统动态振荡响应的高分辨率经验映射方法最近被考虑用于处理数据间隙及其时空补偿。虽然虚拟设计的信号数据不是监测系统的真实条件，但可以通过实施这些数据来客观地研究区域间振荡模式的运动特征和主导路径。本文展示了应用广域测量的时空插值来补偿数据间隙和降低的时空分辨率以进行模态分解。经验模式相干性对密度因子中数据的分裂和聚类的贡献也被呈现到分类区域。该方法涉及经验模式分量的时空高分辨率插值，用于在固有时间尺度上分裂密切相关的振荡模式，保留其多元波形特征。因此，导出了具有退化时空分辨率的遥感动态响应的高分辨率经验观察图，以研究广域振荡模式的观测和主导路径。所提出的方法在数值上应用于 IEEE 16 发电机 68 总线测试系统，以有效定义区域间振荡模式的经验观察图。导出用于研究广域振荡模式的观测和主导路径。所提出的方法在数值上应用于 IEEE 16 发电机 68 总线测试系统，以有效定义区域间振荡模式的经验观察图。导出用于研究广域振荡模式的观测和主导路径。所提出的方法在数值上应用于 IEEE 16 发电机 68 总线测试系统，以有效定义区域间振荡模式的经验观察图。