Transformers predictive maintenance tools
Value:
Risk evaluation gives the operator full information about the status of their transformer fleet and allows to plan maintenance accordingly. Early fault detection minimizes repair costs.
Motivation:
With time the need for diagnostics, maintenance and repairs of transformers fleet increase. Frequent measuring diminishes the risk of transformers breakdowns but often requires costly outages off the installation. Using a combination of statistical and physical models describing the status of the transformer we can optimise the schedule for maintenance outages. Additionally, the system cost of each maintenance outage is calculated which allows for risk-benefit analysis in maintenance planning.
Secondary task of predictive maintenance is to detect failures in their early stage, before they develop into a costly breakdown. Using the same statistical and physical models we can model the operation of the transformers and detect when they deviate from typical operating conditions.
Innovation:
Maintenance outage cost calculation in a grid system under stochastic operating conditions. Combination of physical and statistical modelling methods for early fault detection.