In electricity circles, it feels like everyone is talking about AI data center energy use and load growth.  

Overall electricity load growth, which was nearly flat for decades, is now predicted to sharply increase. A December 2023 report from consulting firm Grid Strategies found that FERC filings in 2023 reflected a near doubling of grid planners’ five-year electricity load growth forecast, with “nationwide forecast of electricity demand [shooting] up from 2.6% to 4.7%.” 

Energy-hungry AI data centers are a major driver of this load growth. A May 2024 study by the Electric Power Research Institute (EPRI) found that AI could drive data centers to consume nearly 10% of the U.S.’ total electricity generation by 2030, up from 2% in 2020. Latitude Media has covered the intersection of AI, energy, and data centers extensively, including on the Carbon Copy podcast.  Even mainstream business media is joining the conversation: the Washington Post did a great podcast on how AI, cleantech manufacturing, and cryptocurrency mining are all adding strain to aging electric grids.

This is not a problem to which I have the answer. However, as co-founder of a company focused on helping organizations (like data centers) plan, procure, and manage clean energy, I see important roles for cloud customers, utilities, and data center companies in meeting rising demand from AI data center energy use while reducing their carbon emissions.

What Cloud Customers Can Do

To avoid a rapid increase in associated carbon emissions, the companies powering the generative AI boom should match their data centers’ energy use with additional clean energy purchases.

Cloud customers – and ideally regulators – need to hold data center companies to high standards. These should include next-generation clean energy goals (e.g., hourly matching or carbon matching rather than annual matching), which should include requirements for additionality. 

This more granular matching, especially with a focus on additionality (adding new clean energy resources to the grid vs. tapping those already online), would help alleviate legitimate concerns about reliability and increased emissions in communities with high concentrations of data centers. Singapore halted all new data center construction between 2019 and 2022 because of concerns that their high electricity demand would strain the grid and negatively impact the city-state’s sustainability goals. Both Singapore and Ireland have published rules in recent years that make new data center construction contingent on things like better energy and water efficiency, the ability to use backup generators, and “the ability to reduce power consumption when requested” (i.e., demand response). 

New data center construction without additional, clean power risks raising power prices and grid emissions. We can expect more moratoriums if we get this next phase of data center growth wrong. 

To their credit, Big Tech has pioneered the concept of voluntary corporate renewable energy purchases, with tremendous follow-on benefits in terms of policy advances and action by other corporate energy users. Now is the time to stay the course – we can’t let the AI mania become an excuse for slipping corporate power procurement standards. That said, cloud customers can only push so far – the electric utilities and their regulatory commissions hold most of the keys in this critical moment.

What Utilities Can Do

The primary suggestion I have for utilities and their regulators is, “while building new generation is a key part of the solution, let’s not treat this AI boom as a land grab for building more rate-based generation.” Business as usual is not a viable option in these unprecedented times. Investor-owned utilities are naturally predisposed to make large capital expenditures to add to their rate base. 

When all you have is a hammer, everything looks like a proverbial nail. Let’s remember that we have other tools in the toolbox. There are many opportunities for utilities to make smaller capital improvements to get more out of their existing infrastructure. Brian Janous (CEO of CloverLeaf Infrastructure) made some great points on this topic in a recent Catalyst podcast). For instance, Janous noted that data centers are effectively microgrids – they have backup generation and storage, and there’s significant opportunity to tap behind-the-meter assets to respond to grid signals.

Utility history wonks will recognize an opportunity to dust off the old “non-wires alternative” playbook, exemplified in the 2013 SCE Local Capacity Requirement procurement, which replaced the 2GW San Onofre Nuclear Generating Station with dispatchable behind-the-meter resources.

Utilities also need to be creative and work with private-sector companies on innovative tariff structures that incentivize load flexibility by passing through wholesale prices and include options to bring-your-own generation (both behind- and front-of-the-meter). Duke Energy provided a great example of this in its recent proposal of a suite of new tariffs to enable large corporate customers to “fund novel technologies like long-duration storage and advanced nuclear as they try to decarbonize.”

What Data Center Companies Can Do

There’s no silver bullet that will solve these load growth challenges for data center companies, utilities, and their regulators. On the one hand, data center companies need better tools to site new facilities in regions with interconnection capacity for both load and supply, procure the right renewable resources, and operate their facilities to minimize both costs and emissions. That’s what Verse focuses on. 

Data center operators also need to combine those tools with other strategies, such as optimizing the timing of compute load for AI model training. Google explained this approach in a 2020 blog post. The overall principle is to move “the timing of many [non-urgent] compute tasks to when low-carbon power sources, like wind and solar, are most plentiful.” Google notes that while they began temporally shifting tasks within a single data center, “it is also possible to move flexible compute tasks between different data centers.”

Other technical innovations could also help, ranging from improved server design and new cooling techniques to more efficient AI chips, like Google’s Tensor Processing Unit (TPU) chips, which Verse’s head of engineering wrote about earlier this year. 

What We Can’t Do — Be Complacent About AI Data Center Energy Use

There’s no question that balancing explosive load growth (driven in large part by AI data center energy use) with reducing carbon emissions is a huge challenge. This is particularly true on aging grids with long interconnection queues, as we’re seeing in many parts of the U.S. However, with the right collaboration (between utilities, regulators, data center companies, and community stakeholders), incentives (from utilities and data center customers), and tools, we can expand powerful new technologies without undermining critical climate ambitions. 

This op-ed was originally posted on MCJ Collective’s substack.

There have been many responses to the Treasury’s initial guidance on the 45V tax credit for green hydrogen production. One of the things that struck our team instantly (probably because of our experience structuring hourly matched clean power portfolios and optimizing utility-scale energy storage resources) was the lack of clarity on the role energy storage can play in allowing for high levels of hourly matching. 

We submitted the following comments to the Treasury advocating for further definition on this point.

Energy Storage Reduces the Cost of Hourly Matching

Energy storage technologies play a critical role in achieving high levels of hourly matching of carbon-free energy. Constructing an hourly matched portfolio without energy storage often requires dramatically overbuilding non-dispatchable renewable energy sources like wind and solar. Analysis by McKinsey has shown that including a portfolio of energy storage technologies alongside renewable energy resources can reduce the cost of achieving 100% hourly matching by more than half (see Exhibit 2 in this article). In key hydrogen markets like ERCOT (Texas), Verse expects to see >10GW of energy storage assets operating by the end of the decade. In a grid with a peak load of 85GW, these assets represent a powerful tool for lowering the cost of achieving high levels of hourly matching. 

We believe it would also be useful for Treasury to clarify in its final 45V guidance how compliance with the three pillars (incrementality, temporal matching, and deliverability), can be met and substantiated. At present it is unclear whether and how energy storage will contribute to compliance with the hourly matching requirement, since the stored electricity will have been generated at a time before it is ultimately used to power the hydrogen production. If energy storage can contribute to hourly matching, Treasury would need to clarify what documentation it will require to substantiate the claims.

We understand that charging an energy storage asset using electricity derived from fossil-fuel generation is contradictory to the goals of the IRA and would not be considered carbon-free energy. The examples below illustrate how energy storage assets can be charged with renewable energy resources, with the support of established operational software solutions. 

Configuration #1: No Storage 

Consider the example of a single day of operations for a 100MW electrolyzer facility that operates as a “flat load” (i.e., the electrolyzer has no ability to curtail its operations). The facility sources its clean power from one offsite wind and one offsite solar facility, as shown in Figures 1 and 2. 

Figure 1: A green hydrogen facility, its power meter, and offsite wind and solar

Figure 2: A green hydrogen facility’s 24-hour flat load (red dashed line), overlaid onto illustrative generation profiles for offsite solar and wind.

In this case, the percentage of the facility’s electricity consumption (aka facility load) served by carbon-free energy (CFE) on this day is 90%. This is also referred to as a 90% “CFE score.” The remaining 10% of the facility electricity consumption is then sourced from grid power.

Configuration #2: Behind-The-Meter (BTM) Energy Storage

Behind-the-meter (BTM) refers to anything that happens onsite, on the energy user’s side of the power meter. Consider an example in which the electrolyzer facility is equipped with a BTM energy storage asset capable of modifying the facility’s electricity usage to match the availability of variable renewable energy supply – in this case, offsite wind and solar generation. The facility operator has control over this storage resource and chooses to optimize it to maximize hourly matching of renewable supply.

Figure 3: A green hydrogen facility, behind-the-meter energy storage asset, the facility’s power meter, and offsite wind and solar

Figure 4: A green hydrogen facility’s 24-hour combined meter reading, which is the summation of the electrolyzer facility load and the BTM energy storage asset (solid red line).

In this case, the BTM storage asset discharges during periods when the variable renewable resources are unavailable to match the facility’s load. The storage asset brings the CFE score up to 100%.

Verse’s interpretation of the current 45V tax credit draft guidelines is that the facility operator (i.e., the taxpayer) would receive credit for 100% hourly matching if they used their BTM energy storage asset in this way. 

Configuration #3: Front-Of-The-Meter (FOM) Energy Storage

Front-of-the-meter (FOM) refers to anything that is offsite from the hydrogen electrolyzer facility, namely on the “grid side” of the facility power meter. Consider a final example, in which we move the energy storage asset from behind the meter to a nearby FOM location in the same “region”, as defined by the 45V geographic matching requirements.

Figure 5: A green hydrogen facility, front-of-the-meter energy storage asset, the facility’s power meter, and offsite wind and solar

Assume the facility operator still has control over the dispatch behavior of this offsite energy storage asset in the same way they did under Configuration #2 and chooses to optimize the storage asset in the same way as in Configuration #2 – again resulting in a CFE score of 100%. 

In this case, shouldn’t the taxpayer receive credit for the same level of hourly matching as in Configuration #2? If it accomplishes the same goal of supplying 100% of the facility’s load with carbon-free energy, the storage asset’s location – whether BTM or FOM – should not matter, as long as it is within the geographic region. Verse’s interpretation of the current 45V tax credit guidelines is that the taxpayer will not receive credit for 100% hourly matching under Configuration #3, which creates an opportunity for clarification of the guidelines.

Clarify the Role of Energy Storage in the 45V Tax Credit: A “Portfolio Approach”

A “portfolio approach” refers to a portfolio of clean energy assets. Verse proposes that the following language be included in the final 45V tax credit guidelines to ensure that energy storage can be used by green hydrogen producers to dramatically reduce the cost of hourly matching:

• Behind-The-Meter (BTM) energy storage will be considered as a load modification to the electrolyzer facility, where the taxpayer is able to use such storage resource to modify their load in service of higher rates of hourly matched clean energy.
• Similarly, Front-Of-The-Meter (FOM) energy storage will be considered as part of the “portfolio” of clean energy resources that a taxpayer can use to achieve high levels of hourly clean energy matching. In the same way that a taxpayer can use a BTM energy storage resource to better match their facility load to their intermittent renewable energy supply, a taxpayer who has contracted for control over the energy dispatch of an offsite energy storage resource will receive the same “load modification” treatment as would be used for a BTM battery, for the purposes of calculating levels of hourly matching.

Risks and Mitigations of Treasury’s Proposed 45V Tax Credit Guidance

Opponents to this proposed structure might raise the following concerns, which Verse seeks to preemptively address below:

• Time Matched EACs: There are alternate ways to deal with the situation outlined above, including with time-stamped energy attributes certificates (EACs) or renewable energy credits (RECs). While the technology is progressing, these certificates have not yet been widely adopted and the nuances of how to track EACs over time as they are “stored” in energy storage assets is complicated by issues like grid carbon-free energy content and round-trip efficiency losses. For these reasons, Verse advocates for the “portfolio approach” outlined above as the simplest way to track hourly matching for large energy users like green hydrogen facilities. 
• Revenue Stacking and Ancillary Services: Opponents to the “portfolio approach” may also argue that the above structure overlooks the nuances of energy storage operations, including the importance of ancillary services^[1], which are the primary revenue streams for utility-scale energy storage assets in restructured markets like ERCOT. As experts in wholesale market optimization of utility-scale storage, the Verse team would respond by pointing to novel structures that simultaneously co-optimize “carbon aware” energy dispatch with ancillary services (link). The revenue stacking “problem” can be readily solved through careful structuring of the energy storage offtake agreement by the taxpayer, and the application of well-established operational optimization software solutions.
• ^[1] “Ancillary services are services that ensure reliability and support the transmission of electricity from generation sites to customer loads. Such services may include load regulation, spinning reserve, non-spinning reserve, replacement reserve, and voltage support.” U.S. Energy Information Agency; Link.

Include Energy Storage in the Final 45V Tax Credit Guidelines

The Verse team would again like to thank the Department of Treasury for its efforts to operationalize section 45V of the IRA and for the opportunity to provide comments. Inclusion and clarification of the use of energy storage assets in the final 45V tax credit guidelines can reduce the cost of achieving high levels of hourly matching, supporting the Biden Administration’s emissions reduction goals and accelerating the energy transition. 

We hope that our comments can aid Treasury in shaping rules that create the pathway to an ascendant domestic green hydrogen industry without adding to power sector emissions.