Indicador de vulnerabilidade operacional para priorização e substituição de transformadores de potência em subestações

• Ano de defesa: 2018
• Autor(a) principal: Schmitz, William Ismael
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Engenharia Elétrica; UFSM; Programa de Pós-Graduação em Engenharia Elétrica; Centro de Tecnologia
• Palavras-chave em Português: Subestações; Substituição de transformadores de potência; Índice de paralelismo; Índice de saúde; PROMETHEE; Substations; Power transformers substitution; Parallelism index; Health index; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
• Link de acesso: http://repositorio.ufsm.br/handle/1/14686

This thesis presents a new methodology for the classification and substitution of power transformers in substations. The thesis proposes the use of the Operational Vulnerability Indicator (OVI), which consists of two groups of criteria, Technical Condition (TC) and Operational Condition (OC). This indicator allows identifying which power transformers from a set of substations have priority for substitution, considering technical-operational information available in the substations. The Technical Condition (TC) is composed by the parallelism index, reserve transformer availability and nominal power. Through criteria such as the parallelism index developed for this work, it is possible to identify the percentage of the load that is assured by a transformer in parallel at the moment of a contingency. The operational condition (OC) addresses the physical situation of the power transformer, typically found in the literature as health index. It assesses factors such as deterioration of the cellulose paper that makes up the insulation and oil, age of the equipment and loading factor, resulting in a life expectancy for the power transformer. The operational vulnerability indicator can be used as an important guide for the strategic planning of the resource application of electric power companies. The methodology is verified through a case study involving real data from 7 substations and 39 power transformers, belonging to a Brazilian electricity company. In the validation of the method, the effectiveness of the proposed method is compared with the ranking obtained through the traditional health index.