Projects

Summary

Distribution transformers are robust machines with long service lives. However, the transition towards decarbonised power generation is driving technological changes that may affect their lifespan. For example, transformers connected to photovoltaic parks and wind farms are exposed to harmonic currents arising from the power electronics associated with generation. As a result, transformers experience increased thermal, mechanical and dielectric stresses. In transformers located at distribution substations, dispersed photovoltaic generation increases fluctuations in the low-voltage network. To continue complying with standards, it is necessary to introduce smart transformers that regulate low-voltage network voltage via an on-load tap-changer (OLTC). The integration of an OLTC can affect transformer reliability.

To face new operating scenarios resulting from the decarbonisation of generation, techniques based on artificial intelligence are being developed to improve decision-making on transformer health and maintenance. That AI must be fed with transformer parameters such as measurements related to the insulating oil or the number of OLTC operations.

Objectives

In this context, the primary objective of the project is the research and implementation of a methodology to determine a transformer health index. This health index will take into account parameters associated with oil quality, insulating liquid pressure and level, hot-spot temperature (HST), number of OLTC operations and the transformer’s electrical operating parameters.

To develop this health index, the project also addresses the following monitoring challenges:

Develop an oil quality sensor based on measurement of the dielectric constant that provides metrics associated with both its real and imaginary parts. Thermally model the transformer in the presence of harmonics and develop a tool that provides information on the HST.

The project will also investigate systems to reduce inrush and connection currents of transformers and how to improve transformer rating calculations using data from thermal modelling.

Ceit’s role

Ceit leads the development of the oil-quality sensor. Ceit’s tasks include the sensor design and associated electronics to obtain metrics of the real and imaginary parts of the dielectric constant. The aim is to develop the concept of a smart fill-plug that will enable oil-quality monitoring not only in new designs but also in transformers already in service.