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、新颖、智能的电网优化体系结构，该体系结构是分布式(低成本)的，能够在电网的多个层次上实时平衡供需。该方法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，将潮流优化程序连接到电网的三层层次：电路、变电站和输电网络，以满足层次结构不同层次上具有不同目标的调度单元组合的要求。智能优点：该项目的主要优点是能够适应分布式资源和存储的高馈入，为决策和电网变量的指数增长提供低成本解决方案，并允许在包括供需弹性在内的低竞价利润下进行发电计划调度。这可以通过实施大规模分布式智能优化体系结构来实现，该体系结构具有协调的分层和分布式控制，可以与网格设备交互。这种方法将使输配网络能够高效地运行，同时满足各种电网水平的目标，同时达到全局最优条件。更广泛的影响：更广泛的影响是，拟议的基础设施有能力改变电网功能，这些功能具有重大的经济效益(提高电网效率和最佳供需弹性)、社会功能(可持续、可靠和有弹性的基础设施)和教育价值(新的课程方法以及培养和留住下一代全球劳动力)，这对发展下一代电网非常重要。

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.