Abstract
The wide area measurement system (WAMS) is widely used in power system and it generates large volume of data. How to use WAMS data to identify the low-frequency oscillation (mode) source in power system remains a great challenge. This paper proposes the correlation data analysis including Pearson correlation coefficient (PCC) and classification decision tree methods, to use the correlation between WAMS and energy management system (EMS) data for low-frequency oscillation (mode) source identification. The case study shows these methods are very efficient and provides a new perspective for processing large volume of WAMS data with EMS data, for low-frequency oscillation (mode) source identification in power system.
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