KeyStone Academy

KeyStone Academy

KeyStone Academy is Shapstone’s research-enablement module within the KeyStone Grid Intelligence platform. It provides universities, research institutions, laboratories, and industry R&D teams with the tools to conduct reproducible experiments, evaluate models, validate new approaches, and advance intelligent power-system research.

Target audiences

• Universities and academic research labs conducting power-system research and student projects.
• National laboratories running large-scale simulation studies and benchmark evaluations.
• Industry R&D teams at utilities and equipment manufacturers validating new technologies.
• Regulatory and policy researchers studying grid resilience, DER integration, and market design.

Key capabilities

• Reproducible experiment environments. Full-stack simulation environments with pinned dependencies and versioned configurations.
• Curated grid datasets. Access to anonymized real-world grid datasets from utility partners and synthetic benchmark models.
• Model evaluation frameworks. Standardized evaluation pipelines for comparing algorithms, architectures, and training regimes.
• Collaborative experiment sharing. Share experiments, results, and findings across research teams with version control.
• Publication-ready outputs. Generate analysis packages and visualizations suitable for academic publication.

How Academy supports research

Academy provides a managed platform where researchers can spin up isolated experiment environments, run large-scale simulations, and compare results against industry-standard benchmarks. Every experiment is version-controlled and reproducible — colleagues can re-run any experiment with a single command and obtain identical results.

Integration with the KeyStone roadmap

Academy is the foundation for the KeyStone platform’s research mission. Insights and models developed in Academy feed directly into Live for production deployment, Twin for simulation studies, and Assure for validation. Academy ensures that the next generation of grid intelligence is built on rigorous, reproducible science.