PMU Data

Smart grid systems require high-quality Phasor Measurement Unit (PMU) data for proper operation, control, and decision-making. Missing PMU data may lead to improper actions or even blackouts. While the conventional cubic interpolation methods based on the solution of a set of linear equations to solve for the cubic spline coefficients have been applied by many researchers for interpolation of missing data, the computational complexity increases non-linearly with increasing data size.

智能电网系统需依赖高质量的同步相量测量单元（Phasor Measurement Unit，PMU）数据，以实现正常运行、控制与决策。PMU数据缺失可能引发不当操作，甚至导致电网停电事故。尽管诸多研究者已将基于求解一组线性方程以确定三次样条系数的传统三次插值方法，应用于缺失数据的插值任务，但该方法的计算复杂度会随数据规模的扩大呈非线性增长。