The electric sector is undergoing rapid change. New business models are emerging as larger portions of the economy, such as transportation, are electrified and intermittent resources and new energy storage solutions are developed and incorporated into the electric grid. Quantum computing can play a part in addressing the increasing complexity as the grid evolves to meet changing requirements and goals of the electric sector.
Applications of quantum computing for the electric sector reported here are informed by analysis of perspectives from the quantum computing industry and electric sector. Applications of quantum computing to optimization, machine learning, and simulation may impact all segments of the electric sector. The most prevalent idea is the application of quantum simulation techniques to aid development of battery technologies. Energy Market Optimization is ranked to have the greatest feasibility and the highest impact over the other ideas.
Expert concepts for the application of quantum computing to the electric sector include application to materials discovery, load modeling and management, and the detection and analysis of faults or outages.
From this analysis, the following observations and conclusions emerged:
- In some cases, the quantum industry and electric sector ascribe differing value to applications of quantum computing. This may represent an opportunity to help quantum companies refine their value propositions and focus on challenges industry finds important. For example, we found that energy experts see more value in being able to predict rare events and rolling blackouts than quantum experts.
- Similarly, our data suggest that the electric sector rates the application of quantum computing as more feasible than the quantum industry finds the same concepts. This may point to a gap in knowledge in quantum computing (by the electricity industry) and expectations by the quantum industry, which has a more conservative outlook. The energy sector may need to temper its expectations regarding quantum solutions disrupting business in the near term.
We identify and assess four key use cases for quantum computing in the electric sector:
- Fault prediction – Using quantum annealing, quantum neural networks, and quantum generative adversarial networks to predict when failures could occur in the energy grid and fix them prior to incident.
- Energy market optimization – Determining when power generators are switched on vs left idle (unit commitment) is a combinatorial optimization problem that quantum computers are capable of solving. The output helps to minimize costs while still meeting demand and is an important calculation for grid operators, energy traders, and consumers.
- Integrated planning and optimization for reliable and resilient grid – Using continuous variable optimization on quantum computers to balance distributed generation, future energy sources, and placement of equipment to increase grid resilience.
- Quantum chemistry simulation for new materials – Quantum simulation of materials show promise for new battery technologies and increase solar cell efficiency.
This report shares ideas and concepts applicable to the power industry as starting point for further exploration of the application of quantum computing in the electric sector.