Weather affects the reliability of distribution networks. Extreme weather conditions can initiate outages, but already normal weather conditions affect the failure of the components in the system, such as cables and cable joints. This study analyses the historical weather and failure records of Alliander, a Dutch Distribution System Operator (DSO). The paper discusses the correlation between failure rates and different weather factors. It presents a predictive model using Basket Analysis. This predictive model is verified using a data set from recent component failures.

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Fault prediction is an important topic for grid operators on improving network performance. Many spontaneous faults in MV cable networks are preceded by a number of self-extinguishing faults. Therefore, the recognition and localisation of self-extinguishing faults will help to reduce the number and impact of persistent faults. The self-extinguishing fault phenomena, as well as the process model to use in fault prediction were studied. By using statistic tools and observing historical measurement records, an algorithm is developed to automatically recognise self-extinguishing faults. This algorithm is implemented in the fault location system of the Dutch DSO Alliander, and proved to be able to recognize all self-extinguishing single phase faults. In addition, a possible method to estimate a global location of self-extinguishing faults is proposed.

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