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This study proposes a WAMS/SCADA data fusion method based on time-series data correlation mining to enhance state estimation in power grids. The method utilizes Pearson correlation coefficients to evaluate data correlation and addresses issues related to time differences and measurement precision. Simulation results demonstrate improved stability and accuracy in state estimation compared to traditional methods, particularly in the IEEE 118 nodes system.
- Author
- starboy105hero
- Language
- EN