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Quantum Computing Can Help Utilities Become More Reliable

Below freezing at breakfast, sweltering by supper, dramatic swings in weather are no longer the purview of small talk. Predicting, accounting for, and reacting to weather are boardroom agenda items that impact safety, security, investment, and the bottom line. And perhaps no industry is more affected than utilities.

The ability to consistently provide reliable, affordable power is strained by the complexity and consequences of catastrophic storms, record-setting cold, and lethal heat waves. In many communities, extreme weather events are pushing infrastructure to its breaking point. Implementing changes to accommodate new energy sources and customer preferences is challenging when the grid itself is in need of modernization. Moreover, as utilities deploy additional technology, such as sensors, they will need greater computational power to harness an increased influx of data.

Thinking creatively and deploying emerging technologies could help utilities serve community needs. According to McKinsey & Company, quantum computing technologies available today can help tackle some of the toughest problems facing the utility industry. These near-term quantum technologies include quantum annealing and quantum-hybrid, which is quantum computing combined with classical computers.

Utilities can now build applications using quantum available via the cloud combined with powerful quantum-hybrid, helping them predict the unpredictable and solve problems outside the reach of traditional computation methods. This could be a game-changer.

Rima Oueid, senior commercialization executive at the U.S. Department of Energy’s Office of Technology Transitions, echoed the importance of near-term applications development at a Center for Strategic and International Studies (CSIS) event. She suggested the grid could provide an opportunity to create a sandbox focused on optimization and contingency analysis. In addition, a recent report from the Quantum Economic Development Consortium (QED-C), a federally established and supported consortium of leading industry stakeholders, identified cases in the electric sector where quantum applications could have the highest impact. They included:

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 and Optimization for Reliable and Resilient Grid. Quantum computers can balance distributed generation, future energy sources, and placement of equipment, which will increase grid resilience.

Forward-thinking utilities and regulators are exploring how today’s quantum computing technology can be integrated with classical computation to help solve challenging problems. According to E.ON, one of Europe’s largest electric utility service providers, quantum technology can modernize an outdated grid to effectively integrate intermittent renewable generation sources. E.ON has used D-Wave’s quantum computing solutions to divide the grid into logical clusters called “communities.” This approach more efficiently manages electricity contributions by allowing energy production and consumption to be managed locally, resulting in improved grid stability and flexibility, and stronger reliance on renewable generation sources. The quantum computer and the hybrid solvers efficiently provided a robust grid-partitioning solution, while the classical computing approach grappled unsuccessfully with the problem.

Power companies face numerous challenges, such as integrating renewable resources, updating outdated infrastructure, and modeling changes in customer energy usage. The push toward electric vehicles (EVs) is putting additional stress on an already taxed grid. Last summer, drivers in California were even asked not to charge their EVs for a time due to grid stress caused by extreme heat. Additionally, the variability of wind and solar calls for more difficult financial and logistical integration.

Quantum computing, particularly that based on quantum annealing, is uniquely suited to address complex problems with millions of variables such as weather, scheduling, and resource allocation. When each variable affects millions of other variables, it is harder to pinpoint effective and feasible outcomes. Utility companies can harness quantum to achieve the precision and resilience necessary to optimize the grid. As an example, in the logistics industry, one quantum-hybrid application supported optimizing Pier 300 at the Port of Los Angeles, increasing deliveries per crane by 60%. Optimizing how containers are sorted, sequenced, and delivered at the port by only a few percentage points can translate into saving tens of millions of dollars a year.

Quantum annealing systems could radically transform the way we understand distribution on the grid and the complex mathematical challenges that arise in transmission and distribution systems. Quantum-hybrid applications also could be used for weather modeling and customer usage predictions. And as new technology comes online, such as distributed energy resources like bidirectional EV charging, quantum is primed to help utilities make useful and timely decisions.

For utilities, reliability is more than a marketing attribute or matter of customer service. Reliable power is essential to keeping people and communities safe, and it enables the economy to thrive. To fulfill their mission to provide essential services, utilities must take a leading role in embracing new technology solutions—like quantum computing—to address and anticipate the complexities of unpredictable optimization challenges.

Murray Thom is vice president of Quantum Business Innovation at D-Wave.

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