We helped a customer in the power domain anticipate faults and reduce maintenance costs of power transformers using its Asset Management System. Explore more.
Power transformers, a key asset of large electrical networks, require regular monitoring of their condition. However, manual monitoring is cumbersome, prone to errors, as well as expensive. The client needed an effective cloud-based solution to manage its requirements.
QuEST developed an effective cloud-based condition monitoring method, called Dissolved Gas Analysis (DGA). The asset information was modelled with OpenDSS and exported as CIM model (XML) files, that was provided as input to the AMS. Data obtained from IEDs that sense gases in insulating oil was simulated using custom applications and pushed continuously to Cloud NoSQL store using REST services. An advanced system based on Pentaho BI was used to determine faults based on IEEE methods (Rogers, key gases methods) & IEC ratio codes were used to perform data trend-based analysis to anticipate incipient faults that are not perceptible.