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Customer satisfaction is one of the important criteria in performance evaluation of electricity distribution companies. From the majority of customers’ point of view, interruption duration is the most important criterion. Electricity distribution companies control and reduce their interruption duration times using set of methods, including preventive maintenance. This paper develops an interruption duration model, considering preventive maintenance action. First, the system interruption data is extracted and organized from the operational dashboard in the Greater Tehran Electricity Distribution Company (GTEDC), and integrated with the meteorological data during the period under review. Then after cleaning the data, linear and nonlinear regression methods were used to model interruption duration. Innovations and contributions of this research can be considered as: 1) data-driven modeling of interruption duration using linear and nonlinear methods, 2) considering the effect of the repair crew locations and urban traffic, in terms of the repair crew travel time to the accident site, 3) considering the preventive maintenance operations history in modeling the interruption duration and sensitivity analysis of interruption duration to preventive maintenance, and 4) analyzing the influence of input features on interruption duration prediction.

Keywords: Preventive Maintenance, Interruption Duration, Distribution Network, Data Mining, Modeling

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