AI Training Data Centres
AI training data centres consume vast amounts of energy due to the intense computational power required to process and train large models. Unlike traditional data centres, their energy usage is highly variable and spikes unpredictably during training cycles and rapidly drops during idle periods. This irregular demand makes it difficult to rely solely on grid power, which is often optimized for steady consumption.
Superdielectrics aqueous zinc batteries provide a flexible, on-site energy buffer that can response rapidly to low-demand periods and capture excess power – and quickly release it when electricity requirements surge. Importantly, being water-based, our batteries are non-flammable.
As a result, data centres can better manage and stabilise energy supply from the grid, and ultimately to transition powered by fully renewable sources.
Please contact us if you wish to find out more.
