Enhancing transformer sustainability through dynamic rating algorithms
This article critically examines how transformer digitalization, through dynamic rating algorithms, can optimize resource use, using a 20 MVA transformer as a case study.
by B. Das
Material production and energy supply are becoming increasingly interconnected. The large-scale deployment of solar energy, wind turbines, electric vehicles, and fuel cells is essential to limit global temperature rise to 1.5°C. However, these technologies require significant raw materials, including steel, copper, aluminum, and concrete, driving demand at an unprecedented rate. Transformers, as critical, long-lasting, and resource-intensive components of the electrical grid, must be designed to address this energy-materials challenge. This article critically examines how transformer digitalization, through dynamic rating algorithms, can optimize resource use, using a 20 MVA transformer as a case study. This article critically examines how transformer digitalization, through dynamic rating algorithms, can optimize resource use, using a 20 MVA transformer as a case study.
#carbon footprint#Digitalization#dynamic rating#load capacity#thermal monitoring
To read the article, subscribe and choose the option which suits you best. We offer both free and paid options, and the registration takes only a minute.
Subscribe to Transformers Magazine
