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Applications of Trend-filtering to Bulk PMU Time-series Data for Wide-area Operator Awareness

Extraction of dominant trend-component forms the
backbone of time-series analysis and forecasting. In power system operation, knowledge of real-time trends in network variables such as bus voltage magnitude, angular separation, line loading is helpful to build situational awareness. In this
work, a multivariate trend filtering scheme is presented to detect, quantify and extrapolate real-time trends in measurement data. The multivariate formulation is necessary so as to provide single framework for wide-area visualization of the network’s state. Using the method, two control center applications are
demonstrated, namely, monitoring of line loading and frequency-data event detection. Performance of the scheme is validated on field data obtained from the wide-area measurement system implemented on the Indian grid. Results indicate application
potential in areas such as dynamic security, stability assessment in addition to general network diagnostics.


Aditya Nadkarni    
Indian Institute of Technology - Bombay

S.A. Soman    
Indian Institute of Technology - Bombay


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