Risk-based Inspection and Maintenance Analysis of Distribution Transformers: Development of a Risk Matrix and Fuzzy Logic Based Analysis Approach
A. M. Sakura R. H. Attanayake, R. M. Chandima Rathnayake
Abstract
A. M. Sakura R. H. Attanayake, R. M. Chandima Rathnayake
Abstract
Distribution transformers (DTs) play a central role in assuring the delivery of crucial functions in electric power distribution systems. To sustain the reliability and availability of an electricity distribution network, it is important to minimize the risk of potential failures of DTs. The risk-based prioritization of inspection, maintenance, and repair tasks enables expensive repairs/replacements, loss of efficiency, loss of revenue, and power loss to consumers to be avoided, by optimizing the utilization of resources. This manuscript demonstrates the use of a fuzzy inference system that enables potential failures of DTs to be prioritized, to prevent the potential failure risk of DTs. The suggested approach enables the risk based on likelihood and the consequence of such failures (i.e., the severity and effects of potential failures) to be calculated. The calculated risks of potential failures enable prioritization of the inspection, maintenance, and repair tasks for DTs at optimal resource utilization. The findings from this study are useful for electric power distribution-related inspection, maintenance, and repair personnel, as well as for asset management professionals.
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Distribution transformers (DTs) play a central role in assuring the delivery of crucial functions in electric power distribution systems. To sustain the reliability and availability of an electricity distribution network, it is important to minimize the risk of potential failures of DTs. The risk-based prioritization of inspection, maintenance, and repair tasks enables expensive repairs/replacements, loss of efficiency, loss of revenue, and power loss to consumers to be avoided, by optimizing the utilization of resources. This manuscript demonstrates the use of a fuzzy inference system that enables potential failures of DTs to be prioritized, to prevent the potential failure risk of DTs. The suggested approach enables the risk based on likelihood and the consequence of such failures (i.e., the severity and effects of potential failures) to be calculated. The calculated risks of potential failures enable prioritization of the inspection, maintenance, and repair tasks for DTs at optimal resource utilization. The findings from this study are useful for electric power distribution-related inspection, maintenance, and repair personnel, as well as for asset management professionals.
Key concepts: Reliability engineering, Risk analysis (engineering), Maintenance engineering, Electric power distribution, Computer science, Transformer, Fuzzy logic, Risk management