Quantum computing use cases in energy
Quantum computing use cases in energy fall into three groups: grid and dispatch optimization, materials chemistry, and oil and gas operations. As of Q4 2026 the examples with a public source are small hardware runs, simulations, emulators, resource estimates, one utility pilot reported without figures, and installed machines without published results, and none is described as running on a grid or at a field.
Updated Q4 2026
Where quantum computing could apply in energy
A 2022 workshop report published through the Quantum Economic Development Consortium, QuEnergy, collected 221 use cases from quantum computing and electric sector experts and assessed the top 17. It names four key use cases: fault prediction, energy market optimization (the unit commitment problem of deciding which generators run), integrated planning for grid resilience, and quantum chemistry simulation for new materials. Energy market optimization ranked highest for both feasibility and impact. The report also found that energy experts rated many concepts as more feasible than quantum experts did, and it advised the electric sector to temper its near-term expectations.
Published examples since then sit in eight areas, with very different levels of evidence.
| Use case | Best public evidence | Evidence level |
|---|---|---|
| Dispatch and unit commitment | Oak Ridge National Laboratory and IonQ, 26 generators over 24 periods (2025) | Hardware experiment at 36 qubits; no classical baseline in the release |
| Grid batteries | Iberdrola and Multiverse Computing pilot in Gipuzkoa (2024) | Pilot with a client; quantum annealer; no figures published |
| EV charging | EDF and Pasqal paper in Physical Review A (2025) | Hardware experiment up to 100 qubits; peer reviewed |
| Battery and cathode materials | Google Quantum AI, BASF and QSimulate estimate for the cathode material LiNiO2 (2023) | Resource estimate |
| Carbon capture materials | TotalEnergies and Cambridge Quantum Computing, CO2 on a metal-organic framework (2022) | Simulation and emulation at 4 to 16 qubits; peer reviewed |
| Fusion | Sandia National Laboratories and Google Quantum AI, stopping power (PNAS, 2024) | Algorithm and resource estimate |
| Seismic imaging and upstream operations | Aramco Europe and D-Wave (2024); Aramco Dammam-7Q emulator (2025); Aramco and Pasqal 200-qubit system (2025, 2026) | Vendor-reported hybrid solver use; emulation; installed hardware with no published results |
| Energy shipping | ExxonMobil and IBM maritime inventory routing study | Modeling study; no experimental results reported |
Grid and dispatch: feasibility demonstrations and one utility pilot
In July 2025 Oak Ridge National Laboratory and IonQ reported a hybrid quantum-classical method for unit commitment, which schedules which generators run, and when, to meet demand at the lowest cost. Using a 36-qubit trapped-ion system with classical computers, the team found solutions for 26 generators over 24 time periods. The release gives no classical baseline or solution-quality figures and does not claim an advantage, and an Oak Ridge researcher is quoted saying it demonstrated feasibility. The work belongs to the U.S. Department of Energy’s GRID-Q project, led by Oak Ridge.
In July 2024 the Spanish utility Iberdrola and Multiverse Computing announced the results of a ten-month pilot on the Gipuzkoa grid, run by Iberdrola’s distribution company, i-DE, on where to install batteries. The pilot used quantum and quantum-inspired algorithms on a quantum annealer and classical hardware, and the announcement says some algorithms matched or outperformed classical benchmarks for grid reliability and voltage control. It gives no figures and no peer-reviewed validation.
EDF and Pasqal researchers published a paper in Physical Review A in March 2025 that uses annealing protocols on a neutral-atom platform for up to 100 qubits and applies them to an EV smart-charging problem built from a real dataset. It describes the method as a scalable, resource-efficient path for hybrid optimization, and its abstract gives no comparison with classical methods.
A July 2025 review from Pacific Northwest National Laboratory covers optimal power flow, unit commitment, economic dispatch and topology optimization. It describes the application as emerging, notes performance discrepancies between theoretical speedups and experimental validations, and asks for rigorous benchmark studies on representative grid test cases. Utility Dive reported in August 2026 that Chattanooga’s utility EPB plans to install a 36-logical-qubit machine later in 2026 for battery siting and dispatch, and describes work at Middle Tennessee Electric, ComEd, Constellation Energy and Duke Energy that is mostly pilots, research support and skills building. It reports no measured pilot results. An EPRI researcher quoted there expects a market tipping point around 2028 to 2030, when processors reach about 100 logical qubits, and an industry analyst expects widespread use to be about a decade away. These are opinions, and TQI cites them as such.
Materials: batteries, carbon capture and fusion
Google Quantum AI’s October 2023 post summarizes resource estimates for three energy problems. With BASF, QSimulate and Macquarie University it estimated tens of millions of physical qubits for four candidate ground-state structures of the cathode material LiNiO2, and said that is out of reach of the first error-corrected computers. With Sandia National Laboratories and Macquarie University it studied fusion stopping power and estimated a cost between the cytochrome P450 and battery cases. Sandia’s August 2024 release on the PNAS paper says current quantum hardware is far from what the calculations require.
The one materials paper with a hybrid run is from TotalEnergies. A 2022 paper by TotalEnergies and Cambridge Quantum Computing authors, published in EPJ Quantum Technology, models CO2 adsorption on an aluminum-fumarate metal-organic framework with a variational algorithm on fragments of 4 to 16 qubits. The runs used noise-free simulation and an emulator of an IBM device, and the paper does not report physical hardware.
Battery chemistry is also an automotive topic, and the automotive guide covers the carmaker studies. The pharma guide explains why exponential advantage in chemistry is still an open question.
Oil and gas operations: vendor-reported use, emulators and installed machines
Aramco’s research center in Europe extended its agreement with D-Wave in June 2024 after about two years of work on seismic imaging, which maps underground rock layers. The team built its own hybrid applications on D-Wave’s cloud solvers and produced its first subsurface maps from tens of gigabytes of seismic data, and the release says the center saw gains over classical computers in time-to-solution and scale. It gives no figures or baselines, and the one-terabyte goal is an aim and not a result.
Aramco’s Upstream Digital Center built Dammam-7Q, a quantum computing emulator on NVIDIA GPUs that handles up to 30 qubits per GPU, and tested a quantum edge detection algorithm for enhancing subsurface images. It is an emulator, not quantum hardware, and the article gives no benchmarks. Aramco also launched on May 18, 2026 a 200-qubit neutral-atom computer from Pasqal at its Dhahran data center, deployed in November 2025, with port logistics, CO2 storage, well placement and rig scheduling as focus areas. The release reports no performance results.
IBM Research and ExxonMobil modeled maritime inventory routing on quantum devices, and IBM’s case study reports no experimental results. Reservoir simulation has no published quantum hardware result.
The nearer-term issue: quantum-safe security
For utilities and operators the earlier quantum question is security. NIST released three post-quantum standards on August 13, 2024 and advised organizations to start integrating them immediately. Utility Dive quotes a Schneider Electric executive saying that waiting on post-quantum cryptography is not a defensible posture.
What the value estimates say, and what they do not
The McKinsey Quantum Technology Monitor, April 2026, estimates that quantum computing could be worth $50 billion to $150 billion by 2035 for electric power and the same range for oil and gas, excluding “black swan” breakthroughs. It treats chemicals separately, at $450 billion to $800 billion, and rates the economic value of electric power and of oil and gas as low for 2025 to 2030 and medium for 2030 to 2035. The report says its value estimates are approximate, overlap with the impact of generative AI and are not additive, and depend on factors unique to each company.
The report also contains a readiness chart built on TQI’s Quantum Index 2025, which scores the 15 most quantum-ready companies in each industry. For energy, European companies total 727 points and rank first, ahead of North America at 240, Asia at 92 and other regions at 72.
How to read a quantum energy claim
- Is there a baseline? The Oak Ridge release, the Iberdrola announcement and the EDF abstract report no figures against classical methods, and the Aramco and D-Wave release gives none either.
- Is it a machine or a result? The Aramco system and the EPB plan are installations. Neither release reports a performance result.
- Hardware, emulator or estimate? Dammam-7Q is an emulator, the TotalEnergies paper used simulators, and the Google estimates assume machines that do not exist yet.
- How big was the problem? 26 generators is a feasibility case, and the LiNiO2 estimate is in the tens of millions of physical qubits.
- Who expects the timeline? A 2028 to 2030 tipping point comes from one EPRI researcher quoted in trade press.
- Has it been peer reviewed? The EDF paper, the TotalEnergies paper and the Sandia and Google paper are published, and the national laboratory review is a technical report. The utility and Aramco items are company announcements.
What an energy company can do now
- Build a cryptographic inventory and plan migration to the NIST standards. This is the step with a published standard and date.
- List the scheduling and dispatch problems that are expensive to solve today, and benchmark the classical solver on them. Unit commitment is the use case the 2022 QuEnergy report ranked highest.
- Follow the resource estimates for materials work, because they say what hardware must exist before a result matters for a battery or catalyst program.
- Ask any vendor or adviser for the baseline, the problem size, and whether the run used hardware or an emulator.
Related guides
The series index lists every industry in this series. Battery work for carmakers is in the automotive guide, shipping in the logistics guide, and the finance guide has the longest list of bank pilots. For company and funding data see TQI Data.
Questions
Is quantum computing used in the energy sector today?
The examples with a public source are small hardware runs, simulations, emulators, resource estimates, one utility pilot reported without figures, and installed machines that have not published results. None is described as operating on a grid or at a field.
Which energy companies are working on quantum computing?
Public sources name EDF, Iberdrola, TotalEnergies, Aramco, ExxonMobil and the utility EPB, with Duke Energy and others building knowledge, and BASF on materials. Partners include Multiverse Computing, D-Wave, Pasqal, IBM, Google Quantum AI and Oak Ridge National Laboratory.
Can quantum computing optimize the power grid?
A 36-qubit run solved a unit commitment problem with 26 generators over 24 periods, and the release gives no classical comparison. A national laboratory review notes performance discrepancies between theoretical speedups and experimental results.
Will quantum computing help batteries and carbon capture?
Resource estimates for a LiNiO2 cathode need tens of millions of physical qubits, and the carbon capture paper used simulators and emulators. Neither is a hardware result for a working material.
How can an energy company find where quantum applies to it?
Start with the dispatch and scheduling problems that are expensive today and with a cryptographic inventory. The Quantum Readiness Check is a short assessment, and TQI Advisory runs fuller assessments.
Sources
- McKinsey Quantum Technology Monitor 2026, April 2026 (electric power, oil and gas and chemicals value estimates, economic value ratings and the readiness chart, which cites TQI’s Quantum Index 2025).
- QuEnergy: exploring the role of quantum computing for the electric grid, Quantum Economic Development Consortium (QED-C), workshop report, November 2022.
- IonQ partners with Oak Ridge National Laboratory, demonstrating quantum power grid optimization advancements, IonQ press release, July 31, 2025.
- Iberdrola and Multiverse Computing announce pilot project success to optimize battery installation in the grid, The Quantum Insider, July 11, 2024 (report of the companies’ announcement).
- Implementing transferable annealing protocols for combinatorial optimisation on neutral atom quantum processors: a case study on smart-charging of electric vehicles, Leclerc et al., arXiv:2411.16656, published in Physical Review A 111, 032611 (March 18, 2025).
- A review of quantum computing technologies in power system optimization, Chen and Vu, Pacific Northwest National Laboratory report PNNL-37598, July 12, 2025.
- Quantum computing and utilities, Utility Dive, August 14, 2026 (updated August 28, 2026).
- Developing industrial use cases for physical simulation on future error-corrected quantum computers, Google Research blog, October 12, 2023.
- Sandia and Google unleash new possibilities in quantum computing, Sandia National Laboratories, August 21, 2024 (PNAS paper on stopping power for inertial fusion target design).
- Modelling carbon capture on metal-organic frameworks with quantum computing, Greene-Diniz et al., arXiv:2203.15546, published in EPJ Quantum Technology 9, 37 (2022).
- D-Wave extends agreement with Aramco Europe to explore quantum-powered optimization of geophysical problems, D-Wave press release, June 6, 2024.
- Dammam-7Q, The Arabian Sun (Aramco), October 12, 2025.
- Aramco and Pasqal launch Saudi Arabia’s first quantum computer and the Middle East’s first commercial quantum computing as a service platform, Aramco, May 18, 2026.
- ExxonMobil and IBM maritime inventory routing case study, IBM.
- NIST releases first 3 finalized post-quantum encryption standards, NIST, August 13, 2024.
Find where quantum applies to your operations
TQI Advisory assesses cryptographic exposure and candidate optimization and materials problems, and scopes each engagement individually.