II-New: A Programmable Data-Driven Testbed for Sustainable Buildings Research

今天的建筑消耗了美国生产的近40%的总能源和75%的电力。因此，使用计算、传感和通信来通过降低能耗、成本和占地面积来使建筑变得更智能、更环保变得越来越重要。当使用计算技术使建筑更智能、更环保时，会出现许多研究问题。例如，我们如何通过将太阳能和风能等可再生能源整合到建筑能源管理系统中来“绿色”建筑？我们如何通过自动执行容易出错的手动任务(如调低恒温器)来减少能源消耗？不幸的是，目前的研究面临着两个关键障碍：无法获得真实建筑的能源使用数据，以及由于安全和舒适度的原因，无法在活建筑中进行实验研究。该项目的重点是通过建设基础设施来收集用于研究目的的真实家庭的匿名能源使用数据，以及建立一个可编程的模拟建筑来实现智能能源管理算法的实验，从而缓解这些障碍。该项目将建立一个可编程的数据驱动的试验台，以实现一系列专注于可持续建筑的研究和教育活动。我们的试验台将由两个组件组成：数据收集组件，用于测量大量各种类型的真实建筑(例如，独户住宅、多户住宅、公寓、公共住房和小型写字楼)，以收集匿名的细粒度实际能源使用和大规模运营数据；可编程智能建筑组件，包括可编程电源和电力负载，使各种能源管理机制能够以安全和可重复的方式进行评估。该试验台将支持各种新颖的研究和教育活动，如设计智能负载管理技术和采用此类技术的强大用户激励；将可再生能源和能源存储集成到智能建筑的能源管理机制中；使用学习和建模来驱动能源数据分析以获得丰富的见解，以及设计智能电网技术的隐私机制，如智能仪表；以及使用该平台进行动手教育和推广到更广泛的社区。该领域的感兴趣的研究人员将获得现实的数据集和试验台，与当地电力公司合作进行实证研究。因此，由试验台实现的研究有可能直接影响实际公用事业公司的电网管理的运营和效率。有一个重要的社区组成部分，可以与更广泛的研究社区共享来自我们仪表化建筑的匿名数据，以及设计规范。

Today's buildings consume nearly 40% of the total energy, and 75% of the electricity, produced by the United States. Consequently, the use of computing, sensing, and communication to make buildings smarter and greener by reducing their energy usage, costs, and footprint has become increasingly important. Many research questions arise when using computational techniques for making buildings smarter and greener. For example, how do we ``green'' buildings by integrating renewable sources, such as solar and wind, into the building energy management system? How do we reduce energy usage by automating error-prone manual tasks, such as turning down a thermostat? Unfortunately, current research is this area faces two key barriers: lack of access to energy usage data from real buildings, and an inability to conduct experimental research in live buildings due to reasons of safety and comfort. This project focuses on alleviating such barriers by building infrastructure to collect anonymous energy usage data from real homes for research purposes, as well as building a programmable mock building to enable experimentation with smart energy management algorithms.This project will build a programmable data-driven test-bed to enable a range of research and education activities focused on sustainable buildings. Our test-bed will be comprised of two components: a data collection component to instrument a large number of real buildings of various types (e.g., single family homes, multifamily dwellings, apartments, public housing and small office buildings) to gather anonymous fine-grained actual energy usage and operational data at scale; and a programmable smart building component that comprises programmable power sources and electrical loads to enable a variety of energy management mechanisms to be evaluated in safe and repeatable manner inside a ``mock" smart building. The test-bed will enable a variety of novel research and education activities like designing intelligent load management techniques and strong user incentives for adopting such technologies; integrating renewables and energy storage into a smart building's energy management mechanisms; using learning and modeling to drive analytics of energy data to derive rich insights, as well as the design of privacy mechanisms for smart grid technologies, such as smart metering; and, using the platform for hands-on education and outreach to a broad community.Interested researchers in this field will have access to realistic data sets and a test-bed to conduct empirical research in collaboration with local electric utility. As a result, the research enabled by the test-bed has the potential to directly impact the operations and efficiency of a real utility's grid management. There is a significant community component to share anonymized data from our instrumented buildings, as well as the design specifications with the broader research community.