Architecture for Quantum-in-the Loop Real-Time Simulations for Designing Resilient Smart Grids
With the power grid growing more complex every day with the inclusion of new sensors and regulatory approvals that enable end-users and small local developers to participate in the grid, it is becoming challenging for conventional smart grid simulation, emulation, and testing technologies to keep up. In this work, we propose that quantum-encoded real-time simulations can be helpful under the new paradigm and operational circumstances to solve optimization problems for power grids. By leveraging the principles of quantum mechanics, the proposed quantum-in-loop (QIL) framework will enable better and faster optimization solutions based on real-world, real-time data streams, facilitating the real-time planning and operations of electrical grids that rely on millions of distributed sensors and controllers. Furthermore, QIL will allow researchers and engineers to assist utilities in designing, developing, and de-risking algorithms to optimize power grid operation and resilience by considering inputs from millions of grid-connected devices. QIL framework is being developed to have a self-limiting triage mechanism, which will help engineers and practitioners identify fundamental physical limits on quantum processors, revealing what quantum algorithms can and cannot do in utility-specific use cases and must continue to count on classical high-performance computing infrastructure.
- Research Organization:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE National Renewable Energy Laboratory (NREL)
- DOE Contract Number:
- AC36-08GO28308
- OSTI ID:
- 1984225
- Report Number(s):
- NREL/CP-4B00-86480; MainId:87253; UUID:d30d1de8-0961-42a8-b52d-5e4ec04308e0; MainAdminID:69710
- Resource Relation:
- Conference: Presented at the 2023 13th International Symposium on Advanced Topics in Electrical Engineering (ATEE), 23-25 March 2023, Bucharest, Romania
- Country of Publication:
- United States
- Language:
- English
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