‘Data Centres, Utilities Collaboration Key To Addressing Grid Constraints’

Schneider Electric has said closer collaboration between data centres and power utilities will be critical to addressing grid constraints, urging alignment of new facilities with microgrids to improve sustainability and reliability.
In a report titled “Looming Power Crunch,” the company said integrating grid supply with on-site renewable energy and battery storage would strengthen resilience. It added that embedding intelligence across infrastructure layers—from grid systems to cooling technologies—would enable data centres to scale for advanced computing without significantly increasing energy consumption.
The report noted that in Nigeria, where the digital economy is a key driver of growth, Artificial Intelligence (AI) workloads are expected to consume a significant share of installed data centre capacity.
It said the relationship between AI and energy is increasingly interdependent, with data centres required to supply power for AI workloads. At the same time, AI technologies can optimise energy use and support decarbonisation efforts.

Country president, Anglophone Africa at Schneider Electric, Ajibola Akindele, said building AI-ready infrastructure in Nigeria requires a focus on resilience and scalability.
“By integrating liquid cooling and collaborating on reference designs, we can ensure that local data centres are prepared for next-generation processors while contributing to a more efficient and sustainable ecosystem,” he said.

The company added that findings from its White Paper 212, “Bending the Energy Curve,” show that improvements in power usage effectiveness could reduce industry energy growth by up to 17 per cent.
According to the report, AI training racks can consume between 100 and 140 kilowatts each, creating high-density and unpredictable energy loads. It noted that increasing power supply alone is not a sustainable solution in markets such as Nigeria, where grid constraints persist.

Schneider Electric said improving efficiency through intelligent energy management is critical to reducing waste and emissions. It highlighted the role of predictive algorithms in forecasting energy demand, enabling operators to adjust consumption patterns and stabilise grid performance.
The report also pointed to the benefits of smart scheduling, which allows energy-intensive workloads to run during periods of lower demand or when renewable energy supply is high, thereby reducing costs.

It added that future data centres in Nigeria are expected to play a more active role in the energy ecosystem by balancing demand through flexible operations.
Schneider Electric noted that AI-enabled facilities could evolve into energy-aware systems that support grid stability while improving operational efficiency.