Abstract
This paper presents the performance of a joint causal and anti-causal (CaC) segmentation method for automatic location of nonstationary parts of power quality (PQ) events. Accurate time allocation of events and sequences of events is an important to automatically analyze disturbances in the future (smart) grid. The new method developed is based on the cumulative sum (CUSUM) algorithm and is applied to a wide set of power quality events to analyze its performance. The main advantage of CaC segmentation is that the location in time of underlying transitions in the power system is accurately estimated.
Published Version
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