Christina Hayes is executive director of Americans for a Clean Energy Grid and Allison Schwartz is global government relations and public affairs leader at D-Wave, a quantum computing company.
Extreme weather events, the changing resource mix, rising customer demands and geopolitical conflicts are increasingly straining the U.S. electric grid and exerting profound and unpredictable effects on the cost of and demand for energy.
Overall electricity consumption is increasing at a furious pace; a report from Grid Strategies says it’s expected to grow 4.7% over the next five years, nearly double what utilities and grid operators expected. New electricity demands from cars, buildings, the onshoring of manufacturing and increased use of cloud computing, are driving this rise in demand. Data centers are being built across the country at such a pace that their energy consumption is expected to double by 2035.
Economy-wide electrification efforts, spurred by the Inflation Reduction Act, will also create new demands on the grid. According to a Princeton study, electricity transmission systems will need to expand an estimated 60% by 2030 and triple in size by 2050.
Meanwhile, our country’s vast network of transmission lines has, in many cases, reached or exceeded its intended lifespan. Our electric sector is at a crossroads as utilities and grid operators work overtime to decarbonize the grid and serve new loads to achieve greater security, reliability and affordability of electric power in the U.S.
Our current approach to grid management and buildout is not up to the task of dealing with such complexity. Developers and policymakers have rightly been considering a number of ways to better manage the grid, including technology to augment existing transmission lines, better known as Grid Enhancing Technologies, or GETs, and new kinds of conducting materials that make lines more efficient. In addition to these technologies, transmission planners, regulators, industry and policymakers must consider new solutions such as exploring how emerging technologies like quantum computing and artificial intelligence can help expand, modernize and upgrade the aging grid.
Quantum and AI can work together to address complex grid problems
The U.S. needs an expanded transmission system, with new well-planned regional and interregional transmission lines. Emerging technologies, including quantum and AI, can help ensure that an improved system is able to meet our evolving energy needs.
Solving transmission problems must be a multi-pronged approach. Together, quantum and AI could expeditiously and efficiently meet new challenges facing the grid, such as updating obsolete electricity infrastructure, efficiently integrating variable clean energy resources and deploying the lowest-cost energy source.
Meeting these new demands will require every tool and technology available — and quantum computing is an important part of the solution.
Optimizing the electric grid and infrastructure projects
Quantum computing in particular is uniquely capable of solving optimization problems. A federally established consortium of quantum industry stakeholders, the Quantum Economic Development Consortium, has examined the role of quantum computing for the grid. Their report identifies cases in the electric sector where quantum applications could have the highest impact.
- Fault prediction – Quantum annealing, quantum neural networks and quantum generative adversarial networks can help utilities better predict energy grid failures, which allows them to fix problems before they occur.
- Energy market optimization – Quantum computers can determine when to switch on power generators and when to leave them idle. This would help minimize costs while meeting customer demand.
- Integrated planning for a reliable and resilient grid – Quantum computers can balance distributed generation, future energy sources and placement of equipment, which will increase grid resilience.
These challenges are not unique to the U.S. Utilities and regulators around the world are exploring how quantum computing can help solve challenges facing the utility industry. For example, E.ON, one of Europe’s largest electric utility service providers, built quantum annealing applications targeted at managing the electricity contributions of prosumers within a grid. While the classical computing approach grappled unsuccessfully with the problem, quantum computing efficiently provided a robust grid-partitioning solution.
Quantum computing could also improve sites for new transmission infrastructure projects. In Japan, the government supported building a quantum-powered application that optimized a construction project by 10%, saving time and money.
Additionally, a recent study by Quantum Quants and the Netherlands Organization for Applied Scientific Research demonstrated that a combination of quantum and classical computing methods provided a robust and scalable solution for the efficient design and management of energy infrastructure.
Legislation must focus on near-term emerging technology solutions
Any policy related to upgrading the grid must include a focus on deploying new technologies to make the most of these significant investments, including near-term quantum computing applications and AI tools that can help tackle electric grid challenges.
There are a number of bills before Congress that could improve development of transmission, move forward the use of technologies that could enhance transmission capacity, and increase grid security, resilience and reliability. In particular, the National Quantum Initiative Act, which expired in September 2023, must be reauthorized and expanded to include near-term quantum application development so the U.S. government can begin using quantum to address today’s complex scenarios, including those facing the electric grid.
Transmission issues will not be solved using yesterday’s way of thinking. A key component of any new policy should be developing and deploying cutting-edge technologies that utilities can begin using in the near term. Emerging technologies like quantum computing and AI are ready today and can be part of the solution to developing an affordable, secure and reliable grid.
