EAGER: Collaborative Research: Empowering Smart Energy Communities: Connecting Buildings, People, and Power Grids

EAGER：协作研究：赋能智能能源社区：连接建筑物、人员和电网

• 批准号: 1637249
• 负责人: Bing Dong
• 金额: $ 17.34万
• 依托单位: University of Texas at San Antonio
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1637249&HistoricalAwards=false
• 关键词: EAGER; Collaborative; Research; Empowering; Smart

1637258 / 1637249 Yu, Nanpeng / Dong, Bing By 2050, 70% of the world's population is projected to live and work in cities, with buildings as major constituents. Buildings' energy consumption contributes to more than 70% of electricity use, with people spending more than 90% of their time in buildings. Future cities with innovative, optimized building designs and operations have the potential to play a pivotal role in reducing energy consumption, curbing greenhouse gas emissions, and maintaining stable electric-grid operations. Buildings are physically connected to the electric power grid, thus it would be beneficial to understand the coupling of decisions and operations of the two. However, at a community level, there is no holistic framework that buildings and power grids can simultaneously utilize to optimize their performance. The challenge related to establishing such a framework is that building control systems are neither connected to, nor integrated with the power grid, and consequently a unified, global optimal energy control strategy at a smart community level cannot be achieved. Hence, the fundamental knowledge gaps are (a) the lack of a holistic, multi-time scale mathematical framework that couples the decisions of buildings stakeholders and grid stakeholders, and (b) the lack of a computationally-tractable solution methodology amenable to implementation on a large number of connected power grid-nodes and buildings.In this project, a novel mathematical framework that fills the aforementioned knowledge gaps will be investigated, and the following hypothesis will be tested: Connected buildings, people, and grids will achieve significant energy savings and stable operation within a smart city. The envisioned smart city framework will furnish individual buildings and power grid devices with custom demand response signals. The hypothesis will be tested against classical demand response (DR) strategies where (i) the integration of building and power-grid dynamics is lacking and (ii) the DR schemes that buildings implement are independent and individual. By engaging in efficient, decentralized community-scale optimization, energy savings will be demonstrated for participating buildings and enhanced stable operation for the grid are projected, hence empowering smart energy communities. To ensure the potential for broad adoption of the proposed framework, this project will be regularly informed with inputs and feedback from Southern California Edison (SCE). In order to test the hypothesis, the following research products will be developed: (1) An innovative method to model a cluster of buildings--with people's behavior embedded in the cluster's dynamics--and their controls so that they can be integrated with grid operation and services; (2) a novel optimization framework to solve complex control problems for large-scale coupled systems; and (3) a methodology to assess the impacts of connected buildings in terms of (a) the grid's operational stability and safety and (b) buildings' optimized energy consumption. To test the proposed framework, a large-scale simulation of a distribution primary feeder with over 1000 buildings will be conducted within SCE?s Johanna and Santiago substations in Central Orange County.

1637258 /1637249 YU，南​​彭 /董，到2050年，世界人口的70％预计将在城市生活和工作，建筑物是主要组成部分。建筑物的能源消耗占用了70％以上的用电，人们在建筑物上花费了90％以上的时间。具有创新，优化的建筑设计和运营的未来城市有可能在减少能源消耗，遏制温室气体排放和保持稳定的电网操作方面发挥关键作用。建筑物在物理上与电力电网相连，因此了解两者的决策和操作的耦合将是有益的。但是，在社区层面上，没有整体框架，建筑物和电网可以同时利用其优化其性能。与建立这样的框架相关的挑战是，建筑控制系统既没有连接，也没有与电网相连，因此无法实现统一的全球最佳能源控制策略。因此，基本知识差距是（a）缺乏一个整体的，多时间的数学框架，可以结合建筑物利益相关者和网格利益相关者的决策，以及（b）缺乏可计算上可吸收的解决方案方法，可在大量可连接的电力网络和建筑物上实施，以填补这一项目，以填补这一范围，以填补这一范围，以填补这一点，以填补这一点，以填补这一范围，以填补新的数学框架，这是一项新颖的效率，这些方法是填补的。经过调查，将测试以下假设：连接的建筑物，人员和网格将在智能城市内实现大量节能和稳定的运营。设想的智能城市框架将提供自定义需求响应信号的各个建筑物和电网设备。该假设将根据经典需求响应（DR）策略进行检验，在该策略中，（i）缺乏建筑物和动力电网动态的整合，以及（ii）建筑物实施的博士计划是独立的和个人的。通过参与有效的，分散的社区规模优化，可以预测为参与建筑物的能源节省，并预测网格的增强稳定操作，从而增强智能能源社区的能力。为了确保广泛采用拟议框架的潜力，将定期通过南加州爱迪生（SCE）的意见和反馈来告知该项目。为了检验该假设，将开发以下研究产品：（1）一种创新的方法，可以建模建筑物群，并嵌入集群动态中的人们的行为以及它们的控件，以便它们可以与网格操作和服务集成； （2）一个新的优化框架，用于解决大规模耦合系统的复杂控制问题； （3）一种根据（a）网格的操作稳定性和安全性以及（b）建筑物优化的能源消耗来评估连接建筑物的影响的方法。为了测试拟议的框架，将在橙县中部的SCE SCE Johanna和Santiago变电站中对分配主要馈线进行大规模模拟。

项目成果

Impact of Occupancy-Based Buildings-to-Grid Integration on Frequency Regulation in Smart Grids

基于占用的建筑并网一体化对智能电网频率调节的影响

• 发表时间: 2018
• 期刊: American Control Conference
• 作者: Dong, D.;Taha, A.F.;Gatsis, N.;Li, Z.;Pipri, A.
• 通讯作者: Pipri, A.

Market and behavior driven predictive energy management for residential buildings

• DOI: 10.1016/j.scs.2018.01.030
• 发表时间: 2018-04
• 期刊: Sustainable Cities and Society
• 影响因子: 11.7
• 作者: Amin Mirakhorli;B. Dong

Occupancy Driven Buildings-to-grid Integration Framework for Large Commercial Buildings

大型商业建筑的占用驱动建筑到电网集成框架

• 发表时间: 2018
• 期刊: 17th International Refrigeration and Air Conditioning Conference at Purdue
• 作者: Dong, B;Fontenot, H
• 通讯作者: Fontenot, H

Occupancy-based buildings-to-grid integration framework for smart and connected communities

• DOI: 10.1016/j.apenergy.2018.03.007
• 发表时间: 2018-06-01
• 期刊: APPLIED ENERGY
• 影响因子: 11.2
• 作者: Dong, Bing;Li, Zhaoxuan;Gatsis, Nikolaos
• 通讯作者: Gatsis, Nikolaos

Buildings-to-Grid Integration Framework

• DOI: 10.1109/tsg.2017.2761861
• 发表时间: 2017-06
• 期刊: IEEE Transactions on Smart Grid
• 影响因子: 9.6
• 作者: A. Taha;Nikolaos Gatsis;B. Dong;Ankur Pipri;Zhaoxuan Li