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: 1637258
• 负责人: Nanpeng Yu
• 金额: $ 8.66万
• 依托单位: University of California-Riverside
• 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=1637258&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余，南鹏/董，冰到2050年，预计世界人口的70%将生活和工作在城市，其中建筑是主要组成部分。建筑物的能源消耗占电力消耗的70%以上，人们90%以上的时间花在建筑物上。拥有创新、优化的建筑设计和运营的未来城市，有可能在降低能源消耗、遏制温室气体排放和维持稳定的电网运行方面发挥关键作用。建筑物与电网是物理相连的，因此了解两者的决策和运营的耦合将是有益的。然而，在社区层面上，没有一个整体框架可供建筑和电网同时利用来优化其性能。与建立这样一个框架相关的挑战是，建筑控制系统既没有连接到电网，也没有与电网集成，因此无法在智能社区层面实现统一的、全球最优的能源控制战略。因此，基本的知识差距是：(A)缺乏将建筑物利益攸关方和电网利益攸关方的决策结合在一起的全面的、多时间尺度的数学框架，以及(B)缺乏易于计算的解决方案方法，适合在大量联网的电网节点和建筑物上实施。在这个项目中，将研究一个填补上述知识空白的新型数学框架，并将检验以下假设：互联的建筑、人员和电网将在智能城市中实现显著的节能和稳定运行。设想中的智能城市框架将为个别建筑和电网设备提供定制需求响应信号。这一假设将与经典的需求响应(DR)策略进行对比，在这些策略中，(I)缺乏建筑和电网动态的集成，(Ii)建筑实施的需求响应方案是独立的和独立的。通过进行高效、分散的社区规模优化，将为参与的建筑节省能源，并预计电网将增强稳定运行，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可能性，将定期向该项目通报南加州爱迪生公司的投入和反馈。为了验证这一假设，将开发以下研究产品：(1)对建筑群及其控制进行建模的创新方法--将人们的行为嵌入到集群的动态中--从而使它们能够与电网运营和服务相集成；(2)解决大规模耦合系统的复杂控制问题的新优化框架；以及(3)从(A)电网的运行稳定性和安全性以及(B)建筑的优化能耗来评估互联建筑的影响的方法。为了验证所提出的框架，将在中央奥兰治县的SCE、S、约翰纳和圣地亚哥变电站内对一条有1000多座建筑物的配电主馈线进行大规模模拟。

项目成果

Risk-Limiting Unit Commitment in Smart Grid With Intelligent Periphery

• DOI: 10.1109/tpwrs.2017.2672939
• 发表时间: 2017-02
• 期刊: IEEE Transactions on Power Systems
• 影响因子: 6.6
• 作者: Chaoyi Peng;Yunhe Hou;N. Yu;Weisheng Wang

Spatio-temporal modeling of electric loads

电力负荷的时空建模

• DOI: 10.1109/naps.2017.8107311
• 发表时间: 2017
• 期刊: 2017 North American Power Symposium (NAPS
• 作者: Shi, Jie;Liu, Yang;Yu, Nanpeng
• 通讯作者: Yu, Nanpeng

Evaluation of frequency regulation provision by commercial building HVAC systems

• DOI: 10.1109/coase.2017.8256215
• 发表时间: 2017-07
• 期刊: 2017 13th IEEE Conference on Automation Science and Engineering (CASE)
• 作者: Yang Liu;N. Yu;Jie Shi;B. Dong;W. Ren;X. Guan

Chordal Conversion Based Convex Iteration Algorithm for Three-Phase Optimal Power Flow Problems

• DOI: 10.1109/tpwrs.2017.2735942
• 发表时间: 2018-03
• 期刊: IEEE Transactions on Power Systems
• 影响因子: 6.6
• 作者: Wei Wang;N. Yu

Modelling, Simulation and Control of Smart and Connected Communities

智能互联社区的建模、仿真和控制

• 发表时间: 2017
• 期刊: Building Simulation 2017
• 作者: Li, Zhaoxuan;Pipri, Ankur;Dong, Bing;Gatsis, Nikolaos;Taha, Ahmad;Yu, Nanpeng
• 通讯作者: Yu, Nanpeng