The laboratory testing of quantum computing (QC) and quantum-inspired computing (QIC) technologies will involve multiple experimental platforms to evaluate their effectiveness against traditional computing methods. One key experiment will focus on benchmarking accuracy, processing time, and the ability to handle complex problem sizes. This will be conducted across different quantum architectures, including gate-based QC systems and quantum annealing approaches. Additionally, hybrid quantum-classical models will be tested to determine their efficiency in solving large-scale optimization problems commonly found in energy system applications. These experiments will use standardized industry datasets to ensure consistency in evaluation and applicability to real-world scenarios.
Another critical aspect of the validation process involves platform-specific testing by industry and research institutions. CESGA, CARTIF and FUJITSU will lead the industry dataset-based laboratory experiments for QIC, assessing its capability in energy management, grid optimization, and renewable integration. Simultaneously, CESGA will focus on improving the accuracy and scalability of gate-based QC systems, leveraging advanced hardware platforms to refine quantum algorithms. Cross-platform comparisons will be conducted to analyze the trade-offs between different quantum approaches, ensuring the most efficient and practical solutions are identified for future deployment in energy systems.
To test quantum-based technologies in energy system applications involves validating quantum computing (QC) and quantum-inspired computing (QIC) against traditional methods, focusing on accuracy, processing speed, and scalability. The evaluation uses industry datasets to assess improvements in problem-solving efficiency and system optimization.
