Guidance for the collection, sampling, cleansing, quality improvement, protection, and utilization of data in the smart grid. Strategy on use of artificial intelligence in the smart grid, including techniques to efficiently obtain high quality data that is informative, representative, and statistically unbiased. Guidance on statistical modeling, interpretable models, and customer or scenario segmentation.
Evaluation of technical attributes of products and services in the context of the evolving smart grid or other relevant ecosystem. Identification of risks and gaps in how products, protocols, and services will perform and interact with the various components of the electric grid and its ecosystem. Comprehensive evaluation of technical potential of products and services in various stages of development, as well as their development processes. Proposal of risk mitigation strategies. Intellectual property review for potential expansion.
Assessment of current and emerging communication networks and protocols for use in evolving smart grid systems, accounting for their interactions with other protocols and grid components. Recommendations for how to optimize and leverage communication to increase grid performance, while scaling to increasing numbers of distributed energy resources with the resulting grid uncertainties.
Design of robust test plans to yield informative results in complex systems with constraints. Design comprehensive range of metrics tailored to specific use cases, and evaluate the system tradeoffs.