A Time Registration Method for Asynchronous Building Electricity Consumption Data Based on the A-PCHIP-iKF Algorithm
Huiyu Yan, Jili Zhang, Liangdong Ma · Buildings · 2025
Building energy consumption data are widely used in various data research and analysis, and data quality is crucial for the accuracy of analysis results. Most existing data quality research focuses on the numerical accuracy of data, while little attention is paid to the temporal accuracy. Time deviations that can be up to thirty minutes are found in the timestamps of the data of a building energy consumption monitoring system. They can result in temporal asynchronism and decreased data accuracy. To correct the time deviations and restore synchronization in data, the A-PCHIP-iKF method is proposed, which integrates time registration and data fusion and utilizes the spatial and temporal correlation to achieve the higher estimation accuracy of correlated time series simultaneously. The results showed that the proposed method has significant advantages over traditional methods in terms of correction accuracy, with 56% RMSE and 60% MAE improvements on the total meter of the building, and can achieve a balance between the correction accuracy, stability, and consistency.