Desenvolvimento de um Sistema de Apoio à Decisão para a Manutenção Preditiva dos ativos de uma Subestação Elétrica - Afonso Neves Caldas (2015)
In a company like EDP Distribuição, the occurrence of faults in a Substation's assets can have dire consequences. It may cause damages to the surrounding equipment and ultimately cause power outages affecting the consumers. EDP Distribuição has developed algorithms to calculate an estimation of: (1) the Health Index, (2) the Failure Probability and (3) the remaining lifetime of a Substation's assets. These metrics give a clear and understandable picture of the asset's state and help in the management of a Substation network. The algorithm has various parameters from different sources like diagnostic tests, routine inspections or online monitoring, which makes it a difficult task to apply this algorithm to all the Substations. A prototype of a Decision Support System was implemented, it uses the necessary inputs to calculate the referred metrics and present them in an understandable and practical way. Using this application, an operator has access to a subset of the network of Substations and can easily check the condition of each Substation's assets. Different potential applications of Data Mining algorithms are also studied to detect patterns in the existing data and provide valuable inputs to the maintenance planning. To the specific case of estimating the Failure Probability various methods were tested and they were able to improve the predictions made by the algorithm created in the company. The final goal is to allow a move from time-based maintenance to a predictive maintenance of the Substations, giving the information needed to apply preventive measures before a fault occurs.