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This letter introduces the application of a data mining method with the purpose of contingency screening, by rapid recognition of hazardous, reoccurring power-system operating conditions. The method, suitable for real-time applications, is demonstrated on the north-western part of the Slovenian power-system, for first-swing stability issues. The presented demonstration consists of two steps: First,...
This paper presents a framework for real-time contingency screening using a situational awareness oriented tool. While some contingencies might have a significant impact on power-system stability, the impact of others is negligible. The consequences of a contingency depend on network conditions. Therefore, fast and effective tools for rapid recognition of hazardous operating conditions from the stability...
The paper describes the use of K-means clustering algorithm to mine the Synchrophasor data from PMUs. PMUs are newly developed tools for monitoring the grid health by measuring grid parameters such as voltage, current, frequency, rate of change of frequency and phase angle with high sample rate and time stamping. The large amount of data produced by PMUs can help the grid operator for stable operation...
A novel empirical data analysis methodology based on the random matrix theory (RMT) and time series analysis is proposed for the power systems. Among the ongoing research studies of big data in the power system applications, there is a strong necessity for new mathematical tools that describe and analyze big data. This paper used RMT to model the empirical data which also treated as a time series...
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