Modified recurrent equation-based cubic spline interpolation for missing data recovery in phasor measurement unit (PMU)

F1000Res. 2023 Dec 18:11:246. doi: 10.12688/f1000research.73182.3. eCollection 2022.

Abstract

Background: 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.

Methods: In this work, a modified recurrent equation-based cubic spline interpolation procedure for recovering missing PMU data is proposed. The recurrent equation-based method makes the computations of spline constants simpler. Using PMU data from the State Load Despatch Center (SLDC) in Madhya Pradesh, India, a comparison of the root mean square error (RMSE) values and time of calculation (ToC) is calculated for both methods.

Results: The modified recurrent relation method could retrieve missing values 10 times faster when compared to the conventional cubic interpolation method based on the solution of a set of linear equations. The RMSE values have shown the proposed method is effective even for special cases of missing values (edges, continuous missing values).

Conclusions: The proposed method can retrieve any number of missing values at any location using observed data with a minimal number of calculations.

Keywords: cubic spline; data pre-processing; data quality; data recovery; interpolation; missing data; phasor measurement unit; smart grid.

MeSH terms

  • Computer Systems*
  • India

Grants and funding

The author(s) declared that no grants were involved in supporting this work.