The accelerated pace of compute, artificial intelligence (AI), and intensive workload deployments globally requires the wholesale redesign of data centers and digital infrastructure.

This redesign has been highly focused on energy management and usage because of the energy demands of the equipment utilized.

The redesign has also prompted a rethink of every electrical component and system, from chip to the grid. This has been dubbed a new period of electrification, as new accommodations are made for greater use of onsite power, grid supports, and bidirectional flows. These developments are seeing data centers become active energy partners in new digital grids, not just unwieldy energy consumers.

Informed decisions

The new process of electrification is not just about sustainability and efficiency; it is also about return on investment. Businesses will need advice and support on how to get from strategy to execution, ensuring electrification delivers value.

Electrification can be seen as an equation, where variables such as the technical, economic, and operational must be optimised and aligned to the business’s key performance indicators (KPI), including financial.

Businesses need support in areas such as process expertise, simulation, digital twins, and techno-economic insights to turn the complexity into clear, confident decisions that support the business vision. The industry has a duty to provide the right advisory services to ensure that the benefits of electrification are accessible to all organizations, large or small.

Changing the load

As accelerated compute has become more sophisticated and capable, requiring new levels of equipment and energy density, data centers have raced to adapt to accommodate.

Energy densities have moved from single-digit kW per rack to the 30-100kW range, with some roadmaps indicating 1MW per rack in the near future, which poses a challenge as grid connections and power distribution solutions scale up to accommodate.

This change has required more sophisticated controls, where AI itself is a key tool in managing more complex systems. Digital design tools, digital twins, and AI-enhanced data center infrastructure management systems (DCIM) are combining to give data center owners and operators new levels of visibility and control to understand how energy is used in real time, identifying bottlenecks or constraints, as well as areas of efficiency and savings.

This builds into a more dynamic, granular picture than ever before about not just sustainability opportunities, but also digital grid integration.

Data center owners and operators are taking the opportunity to look at every aspect of energy management to increase efficiency and resilience while also being responsible energy consumers.

Chip to grid

It has been forecast that by 2027, up to 40 percent of AI data centers will be energy constrained. With such pressures on large energy users, the need for greater resilience and also greater self-reliance, data centers are looking to on-site generation, energy storage, and other techniques to ensure they can respond appropriately to calls for demand-side management.

This requires new infrastructure and energy systems.

Among the solutions being proposed are Energy Parks. Often misunderstood as alternative power plants or niche workarounds, these campus-scale power ecosystems are designed specifically for their load profile, reliability needs, and growth trajectory. They are a pragmatic response to systemic grid constraints where developers cannot wait years for interconnection, or when reliability requirements exceed what the grid can guarantee.

Diesel generators are being phased out in favour of onsite renewable energy sources (RES), battery energy storage systems (BESS), and fuel cells. In conjunction, smart UPS estates can provide storage and balancing capacity to grids too.

These new capacities and assets can become part of the grid ecosystem, supporting wider efforts for load management and RES adoption. Accelerating RES adoption on a wider scale will be a net contributor to national energy decarbonization strategies.

AI for power management

This change in capability supports the requirements of AI workloads, which are often higher density, requiring more sophisticated distribution and management, and new support systems such as facility-wide liquid cooling.

The new systems are geared for extreme continuous loads that can also support surge demand.

AI has accelerated this new wave of electrification as training AI clusters demands massive, stable, high-quality power supply. This requires the ability for flexible load scheduling. AI’s ability to optimize energy usage through constant monitoring and analysis means data centers can use AI models to optimize their energy usage and grid interaction.

Another key benefit is that as process electrification increases throughout the data center, and large energy users generally, it introduces greater opportunity for asset lifecycle management (ALM). Even as electrified processes are more efficient, reliable, and predictable, ALM brings data center resilience and availability to new levels, moving from reactive to predictive maintenance, ultimately paving the way for prescriptive maintenance. ALM brings further benefits for sustainability and reduced waste, as well as optimization.

Grid optimization

With these sophisticated electrification capabilities, data centers can adapt power draw flexibly based on grid demand and conditions, as well as provide grid stabilization services. Data centers can participate in demand response markets, with BESS and smart UPS estates becoming grid assets.

Data centers can act as virtual power plants (VPP), leveraging the capabilities of Energy Parks to support utilities by shielding them from the load variance of today’s most demanding compute workloads, allowing grids time to modernize without undue stress.

This level of electrification means data centers can potentially sell surplus power generated onsite, for example from RES. There are proposals to match compute cycles with RES output for maximum efficiency and sustainability.

Closing efficiency loops

With the increased use of closed-loop systems such as liquid cooling systems and a move away from evaporative systems, there is greater scope for heat recovery. The new drive for electrification facilitates this, as the increasing use of heat pumps in cooling architectures allows for a higher quality in recovered heat, reducing the requirement for additional conditioning before reuse.

Sustainability implications

There are implications beyond data centers for this new wave of electrification. Operators can potentially enjoy new revenue streams from grid services, as well as reduce reliance on fossil fuels in generation and backup. They also enjoy new levels of resilience that will impact the services and service level agreements (SLA) that can be offered.

For regulators, they need to take into account data centers becoming active participants in energy strategy. New market structures and rules would be needed, recognizing flexibility and grid services.

For energy systems generally, this electrification directly supports accelerated RES penetration, as well as linking and supporting AI-optimization for grid efficiency and orchestration. Data center electrification also provides a blueprint for how to encourage all large energy users to become active grid participants in the future.

Holistic transformation

The current transformation of energy systems through electrification is showing how a holistic approach to energy from chip to the grid and beyond is supporting sustainability and efficiency efforts across the board.

Data centers have an opportunity in electrification to not only improve their own capabilities, but in doing so also support national strategies to decarbonize, improve efficiency and flexibility, and accelerate RES penetration. Serving as a blueprint, these efforts can raise overall standards among large energy users everywhere.