A PROBABILITY DISTRIBUTION APPROACH TO DESCRIBE CUSTOMER COSTS DUE TO ELECTRIC SUPPLY INTERRUPTIONS

Abstract

Reliability worth assessment is an important aspect of power system planning and operation. An equally important issue is how to utilize customer costs of electric supply interruption as surrogates to appropriately quantify reliability worth. The objective of this research work was to develop a practical alternative to the conventional customer damage function (CDF) method, to describe the interruption cost data. The alternate technique is designated in this thesis as the probability distribution approach. The fundamental cost data utilized in this thesis comes from the 1991 cost of interruption study performed by the Power Systems Research Group at the University of Saskatchewan which surveyed residential, agricultural, commercial and small industrial customers. This project was sponsored by the Natural Sciences and Engineering Research Council of Canada and eight participating utilities. The probability distribution cost model developed in this thesis is capable of recognizing the dispersed nature of the outage cost data and can be used in a wide range of studies in each electric power system functional zone and hierarchical level. The generation of a three dimensional sector customer damage function, which describes the cost distribution patterns as a function of outage duration, is illustrated. A Monte Carlo simulation approach is utilized to estimate the Interrupted Energy Assessment Rate (MAR) using the two different cost modeling approaches. The analysis clearly shows that the MAR estimated using the distribution model is considerably larger than the value obtained using the CDF method. This thesis also illustrates the application of the MAR in conjunction with the various system operating and reliability data to conduct HLI cost / benefit assessments. The procedure is demonstrated using a small hypothetical test system.