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: 1309911
• 负责人: Sukumar Kamalasadan
• 金额: $ 34万
• 依托单位: University of North Carolina at Charlotte
• 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 2017-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1309911&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.

这项研究的目的是开发一种高性能的小说和智能的网格优化结构，该结构是分布（低成本），并在电动电网的多个级别上实时平衡供求。该方法是使用拟议的集成的近似近似近似动态编程和动态随机约束最佳功率流方法来链接电网三层层次结构的功率流优化程序：电路，变电站和变速器网格，以满足派遣单位投资组合的要求，并满足层次不同目标的要求。知识分子的优点：该项目的关键优点是提出的方法适应分布式资源和存储的高供稿的能力，为决策和网格变量提供了低成本的解决方案，并允许以低竞标利润的速度派遣生成时间表，包括供应和需求弹性。通过使用可以与网格设备进行交互的协调层次结构和分布式控件，实现大量分布的智能优化体系结构，这是可能的。这种方法将使传输和分销网络能够同时实现各种网格级别的目标，并实现全球最佳条件。更广泛的影响：更广泛的影响是拟议的基础设施改变具有实质性经济（提高网格效率，最佳供应和需求弹性）的功率网格功能的能力，社会（可持续，可靠和弹性的基础架构）和教育价值（新的课程方法和下一代全球劳动力）的能力是发展的重要性。