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Abstract:
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Environmental disturbances often cause failure or malfunction of assets and related outage events. However, it is quite common that the failures cannot be identified as being caused by a disturbance based on the data, due to the limited information available at the time of data compilation, time constraints, or personnel's insufficient training. The ability to label an outage event reliably as one caused by a disturbance is a key pre-requisite for analytic activities such as risk modeling, outage detection, prediction and management. Change-point methods play an important role in this process, enabling efficient identification of disturbances and establishment of temporal boundaries. We introduce a methodology for disturbance identification and illustrate its use in conjunction with complex processes governing weather-related outages, which include handling spatio-temporal effects, and outliers. We also discuss the use of this methodology for probabilistic labeling of outage service tickets.
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