This paper focuses on issues arising from the need to automatically analyze disturbances in the future (smart) grid. Accurate time allocation of events and the sequences of events is an important part of such an analysis. The performance of a joint causal and anti-causal (CaC) segmentation method has been analyzed with a set of real measurement signals, using an alternative detection technique based on a cumulative sum (CUSUM) algorithm. The results show that the location in time of underlying transitions in the power system can be more accurately estimated by combining CaC segmentation methods.
