EAGER: Adaptive Dynamic Programming for Residential Energy System Control and Management

EAGER：住宅能源系统控制和管理的自适应动态规划

• 批准号: 1027602
• 负责人: Derong Liu
• 金额: $ 11.9万
• 依托单位: University of Illinois at Chicago
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1027602&HistoricalAwards=false
• 关键词: EAGER; Adaptive; Dynamic; Programming; Residential

This crossdisciplinary proposal aims to apply new intelligent optimization methods to the challenge of intelligent price-responsive management of residential energy use, with an emphasis on home battery use connected to the grid. There has been considerable discussion of the importance of distributed energy storage, including batteries in the home, as a way to create more price-responsive demand and as a way to assimilate more wind power more effectively into the grid. However, to make the best possible use of such batteries for the benefit of the grid, with time of day pricing signals, is a difficult multistage stochastic optimization problem ? also known as a dynamic programming problem. Interest in approximate dynamic programming (ADP) has grown in the power sector, and a few applications have appeared for generators and grid management, but this would be the first application to price-responsive residential demand of any kind. Broad Impacts: This project would be in helping the PI ? a major contributor in ADP, with a strong background in control theory, and strong involvement in IEEE outreach activities and partnerships with China ? make a transition to the intelligent grid areas, where a new type of crossdisciplinary background is badly needed. The need for more storage in the grid is a critical obstacle to greater use and benefit from wind. At present, in the PJM system, a megawatt of wind power requires 0.87 megawatts of new fossil fuel generation to back it up, imposing a huge barrier to its economics and to its use; more storage could eliminate the need for backup. Many are hoping that storage in plug-in hybrid cars can solve this problem, but economically profitable batteries in the home could be deployed more quickly. The necessary 5-minute price signals are available in most leading power regions in the US, and MidWest ISO (where this university is located) has made a special commitment to the kind of price-based management which would make it feasible to deploy this kind of solution.

这个跨学科的提案旨在应用新的智能优化方法来应对住宅能源使用的智能价格响应管理的挑战，重点是连接到电网的家庭电池使用。对于分布式能源存储（包括家用电池）的重要性，人们已经进行了相当多的讨论，认为这是一种创造更多价格响应需求的方式，也是一种更有效地将更多风能吸收到电网中的方式。然而，为了最大限度地利用这些电池来造福电网，在每天的时间定价信号下，是一个困难的多阶段随机优化问题吗？也称为动态规划问题。对近似动态规划（ADP）的兴趣已经在电力部门增长，并且出现了一些用于发电机和电网管理的应用，但这将是第一个应用于任何类型的价格敏感型住宅需求。广泛的影响：这个项目将会帮助PI ？ADP的主要贡献者，在控制理论方面有很强的背景，并积极参与IEEE的推广活动和与中国的合作？向智能电网领域过渡，急需一种新型的交叉学科背景。电网中对更多存储的需求是风能更大使用和受益的关键障碍。目前，在PJM系统中，一兆瓦的风力发电需要0.87兆瓦的新化石燃料发电来支持，这对其经济性和使用造成了巨大的障碍；更多的存储空间可以消除对备份的需求。许多人希望插电式混合动力汽车的储能系统可以解决这个问题，但经济上有利可图的家用电池可以更快地部署。必要的5分钟价格信号在美国大多数主要电力地区都是可用的，中西部ISO（这所大学所在的地方）已经对基于价格的管理做出了特殊的承诺，这将使部署这种解决方案成为可能。