AIS: Collaborative Research: A Novel Intelligent Grid Optimization Architecture Using Hierarchical Multi-Agent Framework for Modern Sustainable Power Grid

本研究的目标是开发一种高性能的新型智能电网优化体系结构，该体系结构是分布式的（低成本），并且在多个电网层面上实时平衡供需。该方法是利用所提出的综合近似动态规划和动态随机约束最优潮流方法，将三层电网：电路、变电站和输电网的潮流优化例程联系起来，以满足不同层次上具有不同目标的调度单元组合的要求。智力优势：本项目的主要优点是所提出的方法能够适应分布式资源和存储的高馈入能力，为决策和电网变量的指数增长提供低成本解决方案，并允许发电计划调度具有低投标边际，包括供需弹性。这可以通过实现大规模分布式智能优化架构来实现，该架构具有可与网格设备交互的协调分层和分布式控制。这种方法将允许输配电网络高效运行，同时满足各种电网级目标，并达到全局最优条件。更广泛的影响：更广泛的影响是拟议的基础设施改造电网功能的能力，这些功能具有重大的经济（提高电网效率和最佳供需弹性）、社会（可持续、可靠和有弹性的基础设施）和教育价值（新课程方法和下一代全球劳动力的产生和保留），这对发展下一代电网很重要。

The objective of this research is to develop a high-performance novel and intelligent grid optimization architecture which is distributed (low-cost) and that balances supply and demand in real-time over multiple levels of the electric power grid. The approach is to link power flow optimization routines across a three-layer hierarchy of power grid: circuits, substations, and the transmission grid using the proposed integrated Approximate Dynamic Programming and Dynamic Stochastic Constraint Optimal Power Flow methodology in order to meet the requirements of dispatching unit portfolios with different objectives at different layers of hierarchy. Intellectual Merit: The key merit of this project is the ability of the proposed method to accommodate high in-feed of distributed resources and storage, provide a low cost solution to exponential increase in decision and grid variables and allow generation schedule dispatch with low bidding margin, including both supply and demand elasticity. This is possible by implementing massively distributed intelligent optimization architecture with coordinated hierarchical and distributed control that can interact with grid devices. This approach will allow the transmission and distribution network to operate efficiently satisfying various grid level objectives simultaneously and yet achieving global optimality conditions. Broader Impact: The broader impact is the ability of the proposed infrastructure to transform the power grid functionalities that has substantial economic (improved grid efficiency and optimal supply and demand elasticity), societal (sustainable, reliable and resilient infrastructure) and educational value (new curriculum methods and generation and retention of next generation global workforce) which is important for developing next generation power grid.