Session: 36-01 Preliminary Design and Structural Optimisation

Paper Number: 152715

Optimisation Applications of Quantum Computing in the Energy Business 

Quantum computing and quantum-inspired computing have emerged as transformative technologies with the potential to revolutionize various fields of engineering, including the energy sector. Despite significant theoretical advancements, direct commercial applications of quantum computing remain limited. At Siemens Energy, we are actively exploring the commercial viability of these technologies within the energy business and engineering domains. This paper provides an overview of early-stage research into the applications of quantum computing for optimization and simulation in the energy industry, emphasizing potential benefits and limitations.

Optimization problems are pervasive in the energy sector, encompassing grid management, power distribution, resource allocation, and supply chain logistics. Traditional methods often struggle with these complex, large-scale mathematical optimization problems (such as Np-hard problems), especially as energy systems grow in scale and intricacy. Quantum computing, designed to solve complex optimization tasks by leveraging principles such as superposition and entanglement, offers promising alternatives. These technologies can potentially find optimal or near-optimal solutions more efficiently than classical algorithms, making them attractive for addressing the multifaceted challenges of modern energy systems.  In addition, many simulation problems can be formulated in new ways offering different ways of simulating problems in areas as diverse as CFD (Computational Fluid Dynamics), materials and emissions.

While the potential benefits of pure quantum computing in the energy business are substantial, practical implementation is not without challenges. Current hardware is still in its nascent stages, with limitations in coherence times, error rates, and scalability. These constraints necessitate the development of error-correcting protocols and hybrid quantum-classical approaches to make these technologies commercially viable.  Despite these limitations, the potential for quantum computing to provide more efficient and accurate solutions to optimization problems can lead to cost savings, improved reliability, and enhanced sustainability of energy systems. Advancements in quantum computing are driving innovation and create new opportunities within the energy sector, fostering a more resilient and adaptive energy infrastructure.

Commercial applications of quantum computing in the energy business are still in the exploratory phase, however, research at Siemens Energy demonstrates their high potential, especially with quantum inspired solutions on Ising machines and annealers, to explore new classes of problems that were previously not possible. This paper offers an overview of such early applications, potential benefits, and limitations paving the way for future research and development in this exciting field.

Keywords: Quantum Computing, Energy Optimization, Quantum Algorithms, Siemens Energy, Quantum-Inspired Computing, Energy Sector, Commercial Applications, Computational Efficiency.

Presenting Author: Nigel Gwilliam Siemens Energy

Presenting Author Biography: Nigel Gwilliam is a Siemens Energy Expert in aerodynamics and heat transfer based in Montreal, Canada. Nigel has worked in aerodynamics and heat transfer in Rolls-Royce and Siemens Energy since 1995 in turbines and compressors. Nigel is part of a group in SIemens Energy Ventures bringing Quantum Computing into the company and finding first commercial applications.

Authors:

Nigel Gwilliam Siemens Energy
Matthew Lang Siemens Energy
Bryan Drossman Siemens Energy
Muhammad Ahmad Siemens Energy
Pranathi Konda Siemens Energy
Klaus Verdnik Siemens-Energy
Rory Macdonald Siemens Energy
Shankar Srinivansan Siemens Energy
Michael Hofstetter Siemens Energy