Iberdrola, parent group of U.S. subsidiary Avangrid, said it has successfully delivered a pilot project with quantum computing company Multiverse Computing which aimed to optimize the installation of grid-scale batteries through algorithms.
The solution from Multiverse uses quantum and “quantum-inspired” algorithms in an effort to select the optimal number, type and locations of batteries on the grid network. The companies say this reduces the costs of adding batteries to the grid and increases network performance.
The 10-month pilot project, which was conducted in Spain by i-DE, Iberdrola’s distribution company, focused on Guipuzkoa’s electricity grid. The companies claim that during the pilot, the algorithms matched or outperformed traditional benchmarks to maximize grid reliability and voltage control. The project used a quantum annealer and classical hardware to test the optimization solution. The algorithm was tested in grids of different sizes, exploring the solution first on small-scale grids and then in larger ones, such as Gipuzkoa’s grid.
Multiverse Computing and Iberdrola say they have implemented solutions to achieve improvements in grid batteries across three key areas:
- Initial cost: Optimize the cost of buying and installing multiple batteries in the electrical grid.
- Voltage control: Maximize the capacity of maintaining voltage levels in the nodes of the gird.
- Reliability: Minimize the impact to customers of power outages in the grid.
The project team used Singularity, Multiverse Computing’s platform for quantum and “quantum-inspired” software, to optimize the network. “Quantum-inspired” techniques use insights and mathematical models from quantum physics in an effort to develop better classical algorithms. The tool enables users without experience in quantum computing to utilize quantum optimizations to boost the speed and accuracy of solutions for complex problems in the energy sector and other industries, Multiverse Computing said.
Avangrid’s U.S. utility subsidiaries include: The Berkshire Gas Company, Central Maine Power Company, New York State Electric & Gas Corporation, Rochester Gas and Electric Corporation, and The United Illuminating Company.
This partnership was hardly the first foray into the quantum computing and power grid realm, and will not be the last.
Announced earlier this year, the Oak Ridge National Laboratory (ORNL) is collaborating with quantum computing company IonQ to help solve power grid challenges and drive infrastructure improvements. In the US Department of Energy-funded project, the two organizations intend to explore how quantum computing technology can be used to modernize the power grid.
The project is focused on addressing the challenges of increasing demand and the proliferation of distributed energy resources, with the need for innovative solutions that can address both optimization and security challenges. In particular, the collaboration is intended to help businesses develop practical quantum hybrid applications that leverage both classical and quantum resources.
Additionally, Atom Computing and the U.S. Department of Energy’s National Renewable Energy Laboratory (NREL) recently announced a collaboration to explore how quantum computing can help optimize electric grid operations.
During a recent IEEE Power and Energy Society general meeting, NREL researchers demonstrated how they incorporated Atom Computing’s atomic array quantum computing technologies into the lab’s Advanced Research on Integrated Energy Systems research platform and its hardware-in-the-loop testing to create a first-of-a-kind “quantum-in-the-loop” capability that can run certain types of optimization problems on a quantum computer.
Initially, NREL and Atom Computing are exploring how quantum computing can improve decision-making on the re-routing of power between feeder lines that carry electricity from a substation to a local or regional service area in the event of switch or line downtime.
Optimization problems such as managing supply chains, devising more efficient transportation routes, and improving electric grid and telecommunications networks are considered “killer applications” for quantum computing, Atom Computing said. These are large-scale problems with numerous factors and variables involved, which makes them well-suited for quantum computers and the way in which they run calculations, according to the researchers.
Keeping power flowing across an electric grid is one example of an optimization problem: Power plants, wind turbines, and solar farms must generate enough electricity to meet demand, which can fluctuate depending on the time of day and weather conditions. This electricity is then routed across miles and miles of transmission lines and delivered to homes, businesses, hospitals, and other facilities in real time.
