Equipment condition assessment and its importance in estimation and prediction of power system reliability

Abstract

Transmission and Distribution Electric Utilities have a vast amount of assets distributed over their system in the form of various equipment. As part of an asset management program, electric utilities keep focusing on the inspection and maintenance activities of these assets to improve system performance, reliability, and to ensure cost-effective expenditures. Therefore methodology that will reflect these inspection and maintenance efforts in terms of overall condition of the equipment is needed. Also techniques are needed to assess the impact of inspection and maintenance activities on the overall reliability of systems performance. To achieve this, a methodology for the assessment of equipment condition and the estimation of the health index for transformers and circuit breakers was developed. After that, a technique to estimate the failure rate from the equipment health index was used. Then an IEEE test case was selected to demonstrate its impact on system reliability indices with the help of a predictive reliability assessment software tool, Milsoft Utility Solution. As part of equipment condition assessment method for transformer and circuit breaker, failure modes and maintenance practices for these equipment was reviewed. Based on this review, parameters were selected for condition assessment which will provide significant information about the equipment condition and will also justify the cost and efforts. For each of the parameters, a score and weight were defined, and guidelines were developed to assign them. Also, ways in which online monitoring systems can contribute to equipment condition assessment were presented briefly. A technique was used to convert the equipment health index into its failure rate. Then an IEEE reliability test case was modeled using the Milsoft software, incorporating this estimated failure rate and studied system’s behavior in terms of reliability indices. It was observed that developing such models will provide more realistic information about the system’s actual performance and will demonstrate the way in which impact of the inspection and maintenance efforts can be accounted.