Load Smoothing in AI Data Centers: The Case for Batteries and Integrated Electrical System Design
As AI data centers drive unprecedented power volatility, developers are increasingly turning to battery energy storage systems (BESS) to stabilize demand and protect gas-fired generation assets. Siemens Energy outlines why traditional grid-scale batteries fall short—and how high-C-rate, marine-grade designs can help operators smooth load, reduce emissions, and optimize gas infrastructure performance.
Danny Clayton and Nico Jansen van Rensburg, Siemens Energy
As artificial intelligence (AI) adoption accelerates, data center power demand is growing at an unprecedented pace. In 2024, data centers consumed over 400 terawatt-hours (TWh) of electricity (around 1.5% of all usage worldwide). This figure is expected to more than double by the end of the decade, reaching 945 TWh .
The electrical grid currently does not have sufficient generation capacity (i.e., dispatchable power) to meet data center demand. Faced with multi-year wait times for utility interconnections and limited transmission capacity, developers are increasingly turning to “behind the meter” approaches by co-locating power generation assets onsite or at a nearby third-party facility.
This trend is creating new opportunities for midstream companies and independent power producers (IPPs). However, the highly volatile load profiles associated with AI data centers also pose unique technical challenges that gas infrastructure operators are not accustomed to handling.
Mitigating electrical transients and “smoothing out” data center load profiles is a complex undertaking that requires specialty know-how and expertise. Today, several strategies are being considered by developers and EPCs.
Battery energy storage solutions (BESS) have emerged as one of several viable options – mainly due to their ability to inject and absorb large amounts of power continuously.
But most commercial BESS systems are not optimized for load smoothing in modern data centers. They are designed for grid applications, which necessitate relatively low charge/discharge rates and large energy storage capacities.
In this article, we outline key considerations when evaluating battery solutions for power smoothing and discuss the importance of adopting an integrated approach to electrical system design.
What Makes AI Data Center Load Profiles Unique?
Modern AI data centers behave differently from traditional IT facilities. They run massive parallel workloads across thousands of graphics processing units (GPUs) and/or accelerators, synchronized through high-speed interconnects. The synchronized interaction between GPUs causes massive power demand fluctuations and dangerous transient conditions in the supply network or microgrid.
In large data centers, demand swings can reach 100 MW or more, occurring multiple times per minute on sub-second timescales. The use of uninterruptible power supplies (UPS) and fast-switching power electronics to supply GPUs exacerbates the problem.
The unpredictable demand profile created by these transients can be challenging for gas turbines or reciprocating engines, which are designed for relatively stable baseload operation. Gas turbines, in particular, operate most efficiently in a narrow load range. Modern turbine ramp rates –while sufficient for grid applications – are typically too slow for the sub-second spikes seen in AI data centers.
Even the most advanced droop control governing in gas turbines cannot handle the rapid changes in frequency. If left unmitigated over time, severe damage can occur, shortening the lifespan of gas turbine units.
Simulations and real-world applications both show that relying on traditional spinning reserves for power smoothing is uneconomical and likely to result in higher emissions, as generating assets are forced to operate outside their optimal fuel-economy range. Inability to closely track load also increases the risk of encountering demand-generation imbalances, which can lead to unit trips or total system collapse.
Power Smoothing With BESS
BESS systems with rapid response capabilities (i.e., ability to inject or absorb power near-instantaneously) are ideally suited for peak shaving and power smoothing in data centers. With BESS in a grid-forming configuration, inverters can quickly detect frequency changes, mitigating the impact of transients on power quality. This is not the case when relying solely on generator controls.
While supercapacitor solutions, such as STATCOMs and E-STATCOMs, offer superior response capabilities compared to batteries, they have limited energy storage capacity. As a result, they are unable to provide long-duration spinning reserve, assist with ramp support, and/or peak shaving – all of which are required in load smoothing applications.
In essence, BESS acts as a “virtual” spinning reserve, ensuring stability during periods of high demand, such as during large language model (LLM) training runs. When demand drops, any excess power from the gas turbine(s) can be immediately absorbed by the batteries. This results in predictable, stable loading on the gas-fired plant, allowing generating assets to run at their maximum fuel-economy point, which minimizes emissions.
Batteries can also improve power plant efficiency by compensating for reduced onsite generation capacity during high daytime temperatures, when mass flow through the gas turbine decreases. The battery pack’s state of charge is then restored during cooler periods, when output capacity increases. This is achieved by implementing an advanced power management system (PMS) that works in concert with the battery management system (BMS).
Not all BESS are Created Equal
Numerous BESS solutions on the market today are technically capable of power smoothing in data centers – though very few are optimized for the application.
Virtually all existing grid-scale BESS installations are designed for long-duration storage, including renewable load shifting, frequency regulation over minutes to hours, and peak shaving or demand response operations on predictable timescales. These applications require batteries with high energy capacity but low charge and discharge rates.
In AI data centers, the dynamic is flipped. Load fluctuations occurring on a sub-second timescale require batteries to respond rapidly and continuously (i.e., 24/7/365). A high C-rate —which is a measure of how quickly a battery can charge or discharge relative to its nominal capacity — is advantageous in this case. The energy storage capacity of the battery in a load-smoothing application is less critical, as transients are usually not sustained for long.
Typical grid-scale, BESS solutions operate around 0.5C. For example, a fully depleted 1 MWhr BESS with 0.5C requires at least two hours to recharge to full capacity. The same BESS with 2C needs only 30 minutes.
For power smoothing in modern data centers, where swings of 100 MW or more can occur in seconds, the low C-rate limits the energy each BESS can absorb. To compensate, the BESS deployment must be exceptionally large. The footprint requirements to accommodate several containerized battery systems can be a limitation for many sites.
Increasing the number of batteries also increased installed costs, requires more balance of plant (BoP) equipment, and increases operation and maintenance (O&M) expenditures.
Thermal management and lifecycle degradation are other challenges. High-rate charging and discharging generate significant heat and accelerate cell wear. Traditional BESS configurations use conservative thermal designs and control algorithms to extend battery life, which further limits how aggressively they can respond to transient loads.
Most systems are designed for 1-2 charge and discharge cycles per day to preserve battery chemistry. Subjecting them to hundreds or even thousands of shallow cycles without proper thermal management can lead to excessive cell degradation, severely impacting the system’s economics and subsequent return on investment (ROI).
BESS inverters are also typically designed for discharge over long periods, and even longer (i.e., slow) recharging times. Again, this is not ideal for data center power-smoothing applications, where inverters will need to switch hundreds or even thousands of times per day between charging and discharging.
How Siemens Energy is Addressing this Challenge
Power smoothing in AI data centers requires BESS systems with unique performance capabilities, including high C-rates and low internal resistance designs optimized for rapid cycling. At the same time, the demanding uptime requirements of facilities (99.99%+) place an extremely high priority on system reliability and thermal runaway protection.
Ironically, these requirements are similar to those in marine applications, where BESS deployments are typical, including ferries, platform supply vessels (PSVs), drilling rigs, and high-power ship propulsion.
Loading on offshore power plants is often highly variable, with transient spikes due to power draws during dynamic positioning, station keeping, drilling, etc. By incorporating BESS into hybrid propulsion systems, loading on gensets can be smoothed, and the need for traditional spinning reserve can be eliminated.
Siemens Energy’s BlueVault battery energy storage was designed specifically for these applications, Fig. 1.
The primary advantage of BlueVault is its unique BESS architecture and purpose-built power electronics, which are designed to accommodate high charge (~2C) and discharge (~4C) rates. In data centers, this allows for a more compact solution (i.e., fewer containers) than conventional onshore BESS solutions, resulting in lower installed and lifecycle costs.
Additionally, BlueVault was designed for rapid and shallow charge and discharge cycles. Thermal degradation is minimized with a closed-loop, water-cooled system designed that dissipates heat from individual cells in three dimensions. The solution also features several passive safety layers and a highly advanced digital condition monitoring system that enables operators to track health and performance at the individual cell level.
BlueVault was first introduced in 2018 and was designed to meet the notoriously onerous global maritime standards. Today, it is operational in 55+ installations worldwide and has been qualified to several standards that are relevant to electrical system design in the U.S. and abroad.
The Advantages of Adopting an Integrated Design Approach
The inherent complexity associated with designing electrical infrastructure for modern data centers makes it advantageous for stakeholders to engage with OEMs and suppliers as early as possible in the project timeline.
While BESS selection is critical, system performance is influenced by several other components, including the converter. Siemens Energy’s Clean Grid Converter (CGC), for example, is specifically tuned to the BlueVault system’s specifications.
Ultimately, BESS selection is just one of several key decisions that must be made when designing the facility’s electrical system. Other factors, such as the transformer’s design and sizing, as well as switchgear arrangements and protection schemes, will also impact performance and lifecycle costs.
Integration of control systems, including the PMS, BMS, substation control, etc., plays a critical role as well. Newer data center developments must incorporate multiple power sources that are synchronized (e.g., grid power, onsite gas or steam generation, solar, wind, geothermal, hydrogen fuel cells, etc.).
Taking a broader view, the industry can benefit by prioritizing a holistic design approach that extends from the power plant through the entire electrical distribution infrastructure and associated control and automation systems.
The limited real-world experience operating AI data centers should compel owners, developers, and EPCs to engage with qualified OEMs who can apply lessons learned from other sectors where electrical system design and BESS implementation are similarly challenging.