Why Battery Storage May Be Crucial to Data Center Development

As AI infrastructure continues to grow exponentially, many are concerned about data center energy usage and its implications for electricity load growth. Some estimates project that data centers could comprise up to 20% of total US electricity usage by 2035. How will the power system meet this rising demand for energy, and can it do so affordably?   

On June 24, 2026, over 300 participants joined a webinar presented by the Clean Energy States Alliance for the Energy Storage Technology Advancement Partnership to discuss the energy demands of artificial intelligence and the critical role that battery storage could play in data center development. During the webinar, David Chernis, Director of Flexible Compute Platforms at CPower, walked through five key reasons why he believes battery energy storage is the solution to rising energy demand from data centers. CPower is developing a new energy layer for AI infrastructure which enables large-scale flexible compute operations to benefit both consumers and the energy grid. 

Reason #1: Batteries tame transient, spiky energy demand 

It is important to start by understanding the power demands of AI data centers. In the early 2020s, most AI data center computing workloads were devoted to training Large Language Models (LLMs), a process that requires substantial amounts of computing power over weeks or months. Now, artificial intelligence mostly deals with “inference workloads,” with customers inputting a question and receiving an answer as the output. These inference workloads are extremely energy-intensive and can spike computing usage from zero to 100% in milliseconds, creating rapid fluctuations in energy demand that can stress energy infrastructure, enough to even snap metal shafts in natural gas turbine generators. Battery storage can “tame” these transient peaks to protect energy infrastructure by supplying stored power during demand spikes. As a bonus, storage can also absorb excess onsite generation, such as from rooftop solar panels during times of low energy demand. 

Reason #2: Protects sensitive AI infrastructure and provides backup power 

AI infrastructure can be extremely sensitive to fluctuations in voltage, a common phenomenon that impacts many advanced manufacturing facilities. To protect against this, many data centers have automatic protocols to shut down equipment when voltage dips. This can lead to huge workload losses. Battery energy storage can smooth out inbound power quality, acting as a buffer between the volatile grid and sensitive data center hardware. Battery storage can also provide backup power during grid outages, further protecting against productivity losses.  

Reason #3: Faster interconnection  

Data centers use a lot of energy, adding strain to an already overburdened grid. This added demand is especially difficult to accommodate during daily and seasonal peak demand hours when grid must call on expensive sources of energy generation to meet demand. Building expensive additional generation and infrastructure to meet these needs would take time, in addition to raising costs for all utility customers and risking grid reliability in the meantime. Data centers that bring their own on-site generation and battery storage may be able to interconnect faster because grid operators don’t have to supply more peak power to accommodate them. Several states have created incentives for faster interconnection for data centers that bring their own on-site generation and storage, which allows the data center to come online faster.   

Reason #4: Cost savings 

Electricity is most expensive during times of peak demand, when energy usage across the grid is at its highest levels. Using on-site battery storage could allow data centers to reduce expensive demand changes, and potentially lower expenses for all ratepayers, by drawing on stored energy when electricity demand is highest. Data centers might also be compensated for supplying excess stored power to the grid during times of peak energy demand through existing demand response programs at the utility and grid level These programs reward quick responses to demand reduction events, providing significant compensation per megawatt of demand reduced. Through managing their demand and exporting surplus power, data centers could help bring costs down for themselves and the grid at large.  

Reason #5: Community benefits 

Communities are often hesitant to welcome hyper-scale data centers because of concerns about rising electricity costs, impacts on grid reliability, water use, and environmental impacts. However, building mid-size facilities paired with battery storage may help lessen community impacts, and potentially provide community benefits by reducing grid strain during peak demand events, such as the hottest and coldest days of the year. The “bring your own capacity” (BYOC) model, in which new facilities arrive with their own integrated energy systems, can transform data centers from liabilities to grid assets; and the host community may be able to benefit if data centers support the development of distributed capacity such as funding the buildout of virtual power plants in the surrounding neighborhoods. The BYOC model for data centers is still evolving, providing state regulatory agencies with an opportunity to incorporate these types of community benefits.  

Addressing data center-driven load growth will continue to be a challenge for the grid, particularly as future energy demand projections continue to skyrocket. Battery storage can reduce the impact these large load customers have on the grid while also providing additional technical and economic benefits to the data center through rapid response to grid needs, faster interconnection, and protections from voltage fluctuation. Battery storage may be one of the best solutions to the AI data center-driven grid capacity constraints many states are experiencing now, since it can provide much need energy capacity and load flexibility. 

Watch the full webinar here: The AI Power Problem: Why Battery Storage is Crucial to Data Center Development