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Federal policy rollbacks won’t stop electricity growth

Rawley Loken is a Senior Managing Consultant, Amber Mahone is a Managing Partner and Tory Clark is a Parter at Energy and Environmental Economics, also known as E3. The electric sector is at a tipping point, with new demands from data centers, electric vehicles, heat pumps and manufacturing driving demand growth at a pace not […]

Rawley Loken is a Senior Managing Consultant, Amber Mahone is a Managing Partner and Tory Clark is a Parter at Energy and Environmental Economics, also known as E3.

The electric sector is at a tipping point, with new demands from data centers, electric vehicles, heat pumps and manufacturing driving demand growth at a pace not seen in decades, highlighting the need for new grid infrastructure investment and integrated resource planning strategies. 

With renewed Republican control of the presidency and Congress, questions abound over which of these trends might be slowed or accelerated. Donald Trump campaigned against the Inflation Reduction Act and Biden-era federal regulations that promote electrification, efficiency and emissions reductions, while asserting goals to increase domestic manufacturing through tariff-based trade policies.

Our analysis of the cumulative impact of technology adoption trends and expected policies on the electric sector, using E3’s U.S. Pathways model, suggests that the recent growth trends are likely to continue and even accelerate under the next administration. We project that U.S. electricity retail sales will grow rapidly and could increase at a rate of 1.6% to 2.2% per year for the next decade under a range of policy and data center growth outcomes reflected in the E3 Low and E3 High scenarios (Figure 1). For comparison, U.S. retail sales of electricity have been nearly flat since 2007, growing at only 0.2% per year.

Figure 1: Total U.S. annual electricity retail sales, historical and projected by scenario

Figure 1: Total U.S. annual electricity retail sales, historical and projected by scenario

Permission granted by E3

While electricity demand is expected to increase across the U.S., the rate of growth will vary widely by state (Figure 2). States with the highest projected electric load growth rates include those with the largest growth in data centers (e.g. Virginia) and those with new grid connected load from the oil and gas sector (e.g. New Mexico). States with aggressive electrification policies (e.g. California, Washington, Oregon, Massachusetts) also see high load growth driven by electric vehicles and heat pumps.

Figure 2: Annual electricity demand growth rate by state for 2023-2035 in the E3 Low scenario E3

Figure 2: Annual electricity demand growth rate by state for 2023-2035 in the E3 Low scenario

Permission granted by E3

The next decade of load growth will be driven by EVs and data centers

Vehicle electrification and data center expansion combined represent 60%-70% of new electricity growth over the next decade in our scenarios, while new industrial and manufacturing growth and heat pumps in buildings are each expected to account for only around 15%-20% of new growth for the U.S. as a whole (Figure 3).

Data center growth rates are based on E3’s recent review of published forecasts. The E3 Low scenario uses the median growth rate from that review to estimate around 32 GW of new data center load by 2035 (240 TWh), while the E3 High scenario uses the high end of the forecast range to estimate 62 GW of new load over same period (460 TWh). Both forecasts assume faster data center growth over the next five years and a gradual slowdown between 2030 and 2035. Interconnecting that much new load to generation will represent a significant challenge for utilities, which is exacerbated by the fact that future data center demand remains highly uncertain.

Electric vehicle sales are likely to increase, even if the next administration repeals the Biden-era federal vehicle emissions standards, due to consumer fuel savings and the potential continuation of state-level policies like California’s Advanced Clean Cars II program, which has been adopted by 11 other states and the District of Columbia, as well as state-specific incentives and low-carbon fuel standards.

The EPA estimates that EV market share for passenger vehicles is still likely to increase from 10% today to 47% by 2032 if current federal policies were rolled back, as is the case in the E3 Low Scenario. If California’s Advanced Clean Cars II program is halted by the Trump administration, EV sales would likely drop further, but the magnitude of the impact will depend on how manufacturers respond. Auto manufacturers may continue to voluntarily comply with many aspects of California’s program, as they did under the first Trump administration. The E3 High Scenario assumes a 68% EV market share by 2032 assuming Biden-era federal policies and state program remain in place.

Figure 3: Incremental electricity demand in 2035 compared to 2023 by end-use

Figure 3: Incremental electricity demand in 2035 compared to 2023 by end-use

Permission granted by E3

Domestic onshoring policies from the IRA and CHIPS Acts could lead to around 30-40 TWh of new manufacturing load by 2035. While the IRA manufacturing tax credits could be in jeopardy under the new administration, many Republican lawmakers have already called for their preservation. Likewise, new proposed tariffs under the Trump administration could lead to an increase in domestic manufacturing over the long-term. However, it is uncertain what the final tariff policy will look like and how much it will influence domestic manufacturing load over the next five to 10 years. Elsewhere in industry, the significant trend towards electrification and grid interconnection of oil and gas loads in the Permian Basin could add almost 90 TWh of new industrial load by 2035.

In buildings, we estimate the increase in demand from heat pumps in buildings to be between 150 TWh and 190 TWh over the next decade. We expect a continuation of the historical upward trend in heat pump space heater sales, even in states that do not require or incentivize heat pumps in their building codes, due to customer economics in states with relatively warm climates.

In 2023, 46% of newly constructed homes were built with heat pump space heating. Even with an anticipated roll-back in IRA customer incentives for purchasing heat pump space heaters in the E3 Low scenario, we do not expect significant changes to space heating adoption numbers at the national scale. However, the Trump administration could seek to weaken finalized DOE standards for residential water heating or other appliances, resulting in higher electricity demand from resistance heating and other appliances as shown in the E3 Low scenario.

Meanwhile, electricity demand for new hydrogen production remains uncertain, but seems unlikely to materialize in a major way over the coming decade. The E3 Low scenario assumes that the IRA 45V clean hydrogen tax credits are repealed or changed such that electrolytic hydrogen is not deeply incentivized, while the E3 High scenario assumes that the 45V tax credit is maintained and around 35 TWh of electrolysis load develops by 2035 based on the DOE database of planned electrolysis projects.

Proactive planning is needed

Regardless of federal climate and energy policy rollbacks over the next four years, the U.S. electric sector will need to plan for load growth at levels not seen for 20 years. The compounding effect of data center load growth and electrification will add load faster than it will be offset by energy efficiency and distributed energy resources in buildings, while new manufacturing facilities will add significant point sources of electricity demand.

Proactive electric grid planning, including integrated system planning of distributed energy resources and distribution, transmission and generation assets, is needed to ensure timely investments in reliable grid infrastructure. Likewise, investments in grid controls, energy efficiency and flexible load management will be important to manage the cost of serving these new electric demands.

While the U.S. has not seen sustained and rapid electric load growth for the past 15 years, we have navigated periods of high growth in the past. With proactive planning, we can turn technological progress to our advantage, minimizing costs and environmental impacts along the way. 

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Dorian LPG Q4 Profit Slashed 79 Percent as Shipping Rates Down

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Trump Signs Memorandum ‘Restoring Maximum Pressure’ on Iran

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Orsted, PGE Make FID on 1.5-GW Wind Farm Near Poland

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Moomba CCS in Australia on Track to Achieve Declared Work Rate, Says Santos

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SSE on track despite stormy weather

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TriMas Completes Arrow Engine Sale

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Linux containers in 2025 and beyond

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Let’s Go Build Some Data Centers: PowerHouse Drives Hyperscale and AI Infrastructure Across North America

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Blue Owl Swoops In As Major Backer of New, High-Profile, Sustainable U.S. Data Center Construction

With the global demand for data centers continuing to surge ahead, fueled by the proliferation of artificial intelligence (AI), cloud computing, and digital services, it is unsurprising that we are seeing aggressive investment strategies, beyond those of the existing hyperscalers. One of the dynamic players in this market is Blue Owl Capital, a leading asset management firm that has made significant strides in the data center sector. Back in October 2024 we reported on its acquisition of IPI Partners, a digital infrastructure fund manager, for approximately $1 billion. This acquisition added over $11 billion to the assets Blue Owl manages and focused specifically on digital infrastructure initiatives. This acquisition was completed as of January 5, 2025 and IPI’s Managing Partner, Matt A’Hearn has been appointed Head of Blue Owl’s digital infrastructure strategy. A Key Player In Digital Infrastructure and Data Centers With multi-billion-dollar joint ventures and financing initiatives, Blue Owl is positioning itself as a key player in the digital infrastructure space. The company investments in data centers, the implications of its strategic moves, and the broader impact on the AI and digital economy highlights the importance of investment in the data center to the economy overall. With the rapid growth of the data center industry, it is unsurprising that aggressive investment fund management is seeing it as an opportunity. Analysts continue to emphasize that the global data center market is expected to grow at a compound annual growth rate (CAGR) of 10.2% from 2023 to 2030, reaching $517.17 billion by the end of the decade. In this rapidly evolving landscape, Blue Owl Capital has emerged as a significant contributor. The firm’s investments in data centers are not just about capitalizing on current trends but also about shaping the future of digital infrastructure. Spreading the Wealth In August 2024, Blue Owl

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Global Data Center Operator Telehouse Launches Liquid Cooling Lab in the UK to Meet Ongoing AI and HPC Demand

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Flexential Partners with Lonestar to Support First Lunar Data Center

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Why DeepSeek Is Great for AI and HPC and Maybe No Big Deal for Data Centers

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Microsoft will invest $80B in AI data centers in fiscal 2025

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John Deere unveils more autonomous farm machines to address skill labor shortage

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2025 playbook for enterprise AI success, from agents to evals

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More 2025 is poised to be a pivotal year for enterprise AI. The past year has seen rapid innovation, and this year will see the same. This has made it more critical than ever to revisit your AI strategy to stay competitive and create value for your customers. From scaling AI agents to optimizing costs, here are the five critical areas enterprises should prioritize for their AI strategy this year. 1. Agents: the next generation of automation AI agents are no longer theoretical. In 2025, they’re indispensable tools for enterprises looking to streamline operations and enhance customer interactions. Unlike traditional software, agents powered by large language models (LLMs) can make nuanced decisions, navigate complex multi-step tasks, and integrate seamlessly with tools and APIs. At the start of 2024, agents were not ready for prime time, making frustrating mistakes like hallucinating URLs. They started getting better as frontier large language models themselves improved. “Let me put it this way,” said Sam Witteveen, cofounder of Red Dragon, a company that develops agents for companies, and that recently reviewed the 48 agents it built last year. “Interestingly, the ones that we built at the start of the year, a lot of those worked way better at the end of the year just because the models got better.” Witteveen shared this in the video podcast we filmed to discuss these five big trends in detail. Models are getting better and hallucinating less, and they’re also being trained to do agentic tasks. Another feature that the model providers are researching is a way to use the LLM as a judge, and as models get cheaper (something we’ll cover below), companies can use three or more models to

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OpenAI’s red teaming innovations define new essentials for security leaders in the AI era

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI has taken a more aggressive approach to red teaming than its AI competitors, demonstrating its security teams’ advanced capabilities in two areas: multi-step reinforcement and external red teaming. OpenAI recently released two papers that set a new competitive standard for improving the quality, reliability and safety of AI models in these two techniques and more. The first paper, “OpenAI’s Approach to External Red Teaming for AI Models and Systems,” reports that specialized teams outside the company have proven effective in uncovering vulnerabilities that might otherwise have made it into a released model because in-house testing techniques may have missed them. In the second paper, “Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning,” OpenAI introduces an automated framework that relies on iterative reinforcement learning to generate a broad spectrum of novel, wide-ranging attacks. Going all-in on red teaming pays practical, competitive dividends It’s encouraging to see competitive intensity in red teaming growing among AI companies. When Anthropic released its AI red team guidelines in June of last year, it joined AI providers including Google, Microsoft, Nvidia, OpenAI, and even the U.S.’s National Institute of Standards and Technology (NIST), which all had released red teaming frameworks. Investing heavily in red teaming yields tangible benefits for security leaders in any organization. OpenAI’s paper on external red teaming provides a detailed analysis of how the company strives to create specialized external teams that include cybersecurity and subject matter experts. The goal is to see if knowledgeable external teams can defeat models’ security perimeters and find gaps in their security, biases and controls that prompt-based testing couldn’t find. What makes OpenAI’s recent papers noteworthy is how well they define using human-in-the-middle

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