Summary
The global electrical sector is constantly evolving due to the increasing energy demand since the industrial revolution of the 19th century. This evolution brings new challenges for companies that generate, transmit and distribute energy. In order to meet these demands, research and technologies are developed aiming at obtaining systems and equipment for the electrical sector with reduced costs, high efficiency and reliability. Reliability and availability estimates are necessary assist in decision-taking and estimate costs related to operation and maintenance of the power system and its equipment, among which the power transformer stands out. Power transformers are essential equipment in the electric power system: they convert voltage levels to interconnect generation, transmission and distribution systems. This work presents a methodology to analyze the reliability of electrical power system equipment with emphasis on power transformers. Therefore, a database is collected concerning the times and failure modes of these equipment. The collected samples are evaluated by parametric probabilistic models largely used in reliability analysis. The Anderson-Darling quality of fit criterion is used to determine which model best fits the study sample. When the probabilistic representation model is found, the maximum verisimilitude and least squares methods are used to estimate the input parameters of the model. Thus, reliability curves, failure rate, risk function and mean time to failure for the equipment were found and analyzed. Besides, it was elaborated the survey of fixed costs related to preventive and corrective maintenance. The curves of preventive, corrective and total were found, as a function of time, using a numerical method for maintenance. An estimate of the optimal time to perform the preventive maintenance was also implemented. Additionally, an economic analysis was elaborated as a function of a maintenance policy. Therefore, the developed methodology allows to analyze the reliability of the power transformers under different aspects and assists decision-taking regarding operation and maintenance.
Additional informations
| Publication type | ISH Collection |
|---|---|
| Reference | ISH2017_367 |
| Publication year | |
| Publisher | ISH |
| File size | 430 KB |
| Pages number | 6 |
| Price for non member | Free |
| Price for member | Free |
