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

AIS：协作研究：利用分层多代理框架实现现代可持续电网的新型智能电网优化架构

• 批准号: 1310709
• 负责人: Reza Ghorbani
• 金额: $ 31.55万
• 依托单位: University of Hawaii
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-06-15 至 2019-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1310709&HistoricalAwards=false
• 关键词: AIS; Collaborative; Research; Novel; Intelligent

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.

本研究的目的是开发一种高性能的新型智能电网优化架构，该架构是分布式的（低成本），并在多个级别的电力网实时平衡供需。该方法是链接在一个三层层次的电网的潮流优化例程：电路，变电站，和输电网使用建议的综合近似动态规划和动态随机约束最优潮流方法，以满足调度单元组合的要求，在不同层次的不同目标。智力优势：该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，为决策和电网变量的指数级增加提供低成本解决方案，并允许以低竞标利润率进行发电计划调度，包括供应和需求弹性。这是可能的，通过实施大规模分布式智能优化体系结构与协调的分层和分布式控制，可以与电网设备进行交互。这种方法将允许输电和配电网络有效地运行，同时满足各种电网级目标，并实现全局最优条件。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，这些功能具有巨大的经济（提高电网效率和最佳供需弹性），社会（可持续，可靠和弹性基础设施）和教育价值（新的课程方法以及下一代全球劳动力的产生和保留），这对于开发下一代电网非常重要。