Multi-source data correction method and system based on interpolation method and time sequence intelligent method
By combining interpolation and time-series intelligent methods, a multi-source data correction method was developed to address the issue of neglecting periodicity, trends, and monotonicity in power grid data acquisition. This method enables accurate and real-time correction of power grid data, thereby improving the operation, maintenance, and monitoring capabilities of the power grid system.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2023-04-12
- Publication Date
- 2026-03-24
AI Technical Summary
Existing technologies fail to effectively consider the periodicity, trend, or monotonicity of data during power grid data acquisition, making it difficult to obtain accurate and real-time corrected data after data interpolation, which affects the normal operation of the power grid system and the accuracy of decision-making.
A multi-source data correction method based on interpolation and time-series intelligent methods is adopted. The k-Means algorithm is used to detect abnormal data, and the abnormal data prediction model is trained by combining time-series prediction method. Abnormal data is predicted and removed according to the data change pattern. Interpolation is performed using fitted curves or neighboring point data to ensure the accuracy and real-time performance of the data.
It improves the accuracy and real-time performance of power grid anomaly data correction, ensures the data quality of power grid system operation and maintenance and monitoring, and reduces the threat of anomaly data to power grid security.
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Figure CN116662841B_ABST
Abstract
Citation Information
Patent Citations
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