1 Abstract--The methodology used to assess the historical reliability performance of a Canadian Utility’s electric distribution system is outlined. Included is an overview of the process used to collect and organize the required interruption data as well as a description of the performance indices calculated for use in the causal assessment. The various component parts of the reliability performance assessment are described. This includes a description of indices comparison between years and to the average at different levels of the system and by outage cause and component failure. Finally, results from the 2004 reliability assessment of the utility’s electric distribution system are summarized and the application of the calculated performance statistics in planning, operating and maintaining distribution systems is described. Index Terms—Distribution system, historical reliability performance, data collection system, causes of interruptions, application of historical data I. INTRODUCTION WO approaches to reliability evaluation of distribution systems are normally used; namely, historical assessment and predictive assessment. Historical assessment involves the collection and analysis of distribution system outage and customer interruption data. It is essential for electric utilities to measure actual distribution system reliability performance levels and define performance indicators in order to assess the basic function of providing cost effective and reliable power supply to all customer types. The distribution system is an important part of the total electrical supply system. This is due to the fact that the distribution system provides the final link between a utility’s transmission system and its customers. It has been reported elsewhere that more than eighty per cent of all customer interruptions occur due to failures in the distribution system [1]. Historical assessment generally is described as measuring the past performance of a system by consistently logging the frequency, duration, and causes of system component failures and customer interruptions. Predictive reliability assessment, on the other hand, combines historical component outage data and mathematical models to estimate the performance of designated configurations. Predictive techniques therefore rely on two basic types of data to compute service reliability: component reliability parameters and network physical configurations. A. A. Chowdhury is with Electric System Planning, MidAmerican Energy Company, Davenport, IA 52801, USA (aachowdhury@midmaerican.com), and L. Bertling is with Royal Institute of Technology, Stockholm, Sweden (lina.bertling@ets.kth.se) The historical data is very useful when analyzed to ascertain what went wrong in the past and therefore correct it, and also as input to predict future service reliability. Both historical and predictive assessments therefore involve the collection of system outage data. Historical models summarize the actual performance of a distribution system during some time period, for example, quarterly, semi-annually or annually. The basic data item in this case is a system failure, which is a component outage or a customer interruption. Each failure event is taken into consideration and analyzed according to causes of failure, duration of outage, area of the system affected. A variety of customer and load oriented system performance indices can be derived by manipulating the recorded data. These indices are very useful for assessing the severity of interruption events. Assessment of past performance is useful in the sense that it helps to identify weak areas of the system and the need for reinforcement. It enables previous predictions to be compared with actual field experience as well as it can serve as a guide for acceptable values in future reliability assessments. A variety of performance indices that express interruption statistics in terms of system customers can be computed using the service continuity data. This paper is concerned with the aspects of historical reliability assessment. It briefly describes the different characteristics of an Automatic Outage Management System (AOMS) used at a Canadian utility for collecting and analyzing the distribution supply interruptions and also presents a summary of service continuity statistics for the Canadian utility distribution system for the five-year period 2000 through 2004. In addition to the analysis by primary causes, analysis of failure data by sub-components that fail on the distribution system and what contributions they represent to the total unreliability also is presented. II. AUTOMATIC OUTAGE MANAGEMENT SYSTEM The Canadian utility of concern in this paper uses its automatic outage management system to collect outage data for its distribution system. The current system was installed in late 1998. The Canadian utility is an integrated utility consisting of generation, transmission and distribution facilities with urban, fringe and rural networks. Analysis was done using AOMS data for the period 2000-2004. The service area is divided into three regions for the purpose of this paper, namely, Region 1, Region 2 and Region 3. The general utility distribution system characteristics are summarized in Table I. A. A. Chowdhury, Fellow, IEEE and L. Bertling, Member, IEEE Distribution System In-Depth Causal Reliability Assessment T 9th International Conference on Probabilistic Methods Applied to Power Systems KTH, Stockholm, Sweden – June 11-15, 2006 © Copyright KTH 2006