IEEE P3378.7

New IEEE Standard - Active - Draft.
This standard define reference architecture covering infrastructure, data resources, tools, model, agent, power application, and performance layers. It specifies technical requirements for data management, computing and network resources, domain capabilities including language, vision, scientific computing, time-series prediction and multimodality, as well as applications in power planning, grid operation, equipment maintenance, and market operation.

This standard provides a reference architecture for large-scale deep learning models in power industry. The reference architecture includes resource pools, architectures, tools, data resources, models, interfaces, industry applications, and service platforms.
This standard specifies requirements for scenario service capabilities, general capabilities, and application maturity, which enables to evaluate the technical maturity and stability of large-scale deep learning models in power industry and determine whether large-scale deep learning models can be smoothly and effectively integrated into existing operations, processes, and systems.
This standard provides a reference for third-party power industry researchers as well as regulatory and evaluation institutions to conduct capacity assessments of large-scale deep learning models in power industry.