Insider Brief:
- E.ON is working to resolve energy grid complexity through quantum computing with IBM to address challenges posed by renewable energy sources and their shifting consumption patterns.
- Quantum algorithms developed by E.ON and IBM calculate energy costs under varying weather conditions, using Qiskit and dynamic circuits to optimize energy pricing and hedging decisions.
- IBM’s developments in quantum computing enable the handling of complex, high-dimensional problems, with hopes of reaching quantum advantage by 2029.
- E.ON advises early adoption of quantum expertise to capture low-hanging fruit and build talent pools, ensuring readiness for competitive advantages as quantum technology matures.
As countries around the world consider how to transition toward a renewable energy future, the landscape of energy management grows increasingly intricate. E.ON, one of Europe’s largest energy companies, serves 47 million customers across 17 countries, operating a 1.6-million-kilometer energy network to ensure homes, hospitals, factories, and transit systems stay powered.
Amid the shift to solar, wind, and electrified systems, the company faces unprecedented challenges. The old models of steady supply and demand have given way to a dynamic and less predictable grid. To address this, E.ON has turned to quantum computing, as detailed in a recent case study with IBM Quantum.
The Energy Grid’s Transformation
E.ON’s mission to ensure reliable energy distribution now involves managing variability in both supply and demand. Renewable energy sources, like solar and wind, introduce an element of unpredictability, while electric vehicles and intelligent systems add further complication to consumption patterns.
As Dr. Giorgio Cortiana, Head of Data & AI at E.ON, puts it, “We are becoming a digital company. Data technology will be essential to help us master the complexity of these systems.” The challenges of procurement and pricing compound this complexity, as E.ON must procure the energy before it’s consumed, often relying on energy derivatives to alleviate any mismatches between supply and demand.
Traditional Monte Carlo simulations–statistical models for predicting outcomes under uncertainty–are used to navigate this pricing landscape as they can account for volatile factors such as weather and usage patterns. However, these classical methods struggle with the many interconnected variables that define modern energy systems.
Quantum techniques come to mind here as a potential solution as the inherent properties of quantum computers, such as superposition, make them well-suited for solving complex, high-dimensional problems. This enables them to uncover patterns and relationships among interconnected variables in a way that can surpass classical solutions.
According to Dr. Piergiacomo Sabino, Quantitative Risk Expert at E.ON, “This requires us to be smart and forward-looking, years in advance. Climate change and black swan events must be part of our model.” To go beyond the limits of classical computing, E.ON has partnered with IBM to explore quantum solutions.
Quantum Solutions for Energy Pricing
In the arena of energy pricing, where variables like weather, consumption, and supply shift unpredictably, the complexity often outpaces classical computation. Enter quantum computing—a tool with the potential to decode these intricate systems. Through quantum algorithms, E.ON and IBM are working to solve one of the sector’s toughest puzzles: predicting the cost of energy under constantly changing conditions.
One such algorithm calculates the costs of offering energy at fixed prices under varying weather conditions. This requires running the algorithm repeatedly to inform hedging decisions. The team used IBM’s Qiskit software, a toolkit for quantum programming, to do so. Early versions of the algorithm were adapted to run on IBM’s 27-qubit quantum computer using a feature called dynamic circuits. This capability allowed the problem to be broken into manageable pieces for computation.
“Using Qiskit for this project was a no-brainer,” said Dr. Corey O’Meara, Chief Quantum Scientist at E.ON. “It’s fantastic and improving more and more.” This work underscores the rapid advancements in quantum computing technology, paving the way for practical applications.
A Vision for Quantum Utility
E.ON’s quantum ambitions extend beyond proofs of concept. Through case studies such as this one, the company is actively working towards achieving quantum utility. As noted in the study, IBM’s developments in error correction provide hope for the company that quantum computers will reach this milestone by 2029.
For E.ON, this represents an opportunity to update energy pricing models, delivering new efficiencies and competitive advantages. Dr. Cortiana advises other organizations to “project yourself a few years into the future and envision the situations where computational capabilities will run short. Ask where quantum can help.”
From Theory to Utility
While demonstrations such as this one lend credibility to the claim that quantum computing holds promise for practical applications, its integration into business processes is still much in its infancy. E.ON’s partnership with IBM is a testament to the importance of collaboration between industries and research institutions to build quantum expertise.
As Dr. O’Meara explains, “I think working at utility scale is the next thing that has to happen for the entire quantum computing field. People have been doing toy models and small-scale proofs of concept with a couple of qubits. That’s going to change.”
