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.

Electricity usage of buildings (including offices, malls and residential apartments) represents a significant portion of a nation's energy expenditure and carbon footprint. Buildings are estimated to consume 72% of the total electricity production in the US. Unfortunately, however, 30% of this energy consumption is wasted. Virtual energy assessment is an approach that can optimize building energy efficiency and minimize waste at a low cost with minimal expert intervention. A virtual energy audit includes a thorough and near real time analysis of different sources of building energy usage, individualized energy footprints of load appliances and devices, and proactive identification of energy holes and air leakages. This project builds a low cost solution that combines the use of non-intrusive single point energy monitoring and low cost IR cameras to provide continuous energy audits. The system will provide continuous virtual audit reports to the landlords or residential users. The system will be deployed in low-income neighborhoods in Baltimore City, Maryland, where poor insulation problems are assumed to be fiscally insurmountable and low cost solutions to determining these issues is important for the landlords. To develop a scalable low cost virtual energy auditing system, this breakthrough research pursues the interfaces of smart building sensing, computing and actuation. The project will be executed under three main research thrust areas. First, it utilizes an autonomous discovery, profiling and rule-based predictive model to capture the relationship between disaggregated power measures and a device's actual usage patterns to pinpoint any abnormal consumption. Second, the PIs develop zero-energy far-infrared imaging sensors for low cost low frequency heat map scanning and air leakage detection. Third, the project engineers and evaluates cyber-physical building sensing system with a control level design perspective for virtual energy auditing that drives the realization of deep energy savings and building efficiency. Additionally, the PIs with collaboration from Constellation will host building energy education projects and workshop where undergraduate, high school, and underrepresented group of students would understand how to design and program energy meters and smart plugs.

This project explores balancing performance considerations and power consumption in cyber-physical systems, through algorithms that switch among different modes of operation (e.g., low-power/high-power, on/off, or mobile/static) in response to environmental conditions. The main theoretical contribution is a computational, hybrid optimal control framework that is connected to a number of relevant target applications where physical modeling, control design, and software architectures all constitute important components. The fundamental research in this program advances state-of-the-art along four different dimensions, namely (1) real-time, hybrid optimal control algorithms for power management, (2) power-management in mobile sensor networks, (3) distributed power-aware architectures for infrastructure management, and (4) power-management in embedded multi-core processors. The expected outcome, which is to enable low-power devices to be deployed in a more effective manner, has implications on a number of application domains, including distributed sensor and communication networks, and intelligent and efficient buildings. The team represents both a research university (Georgia Institute of Technology) and an undergraduate teaching university (York College of Pennsylvania) in order to ensure that the educational components are far-reaching and cut across traditional educational boundaries. The project involves novel, inductive-based learning modules, where graduate students team with undergraduate researchers.

1329875 (Hu). Despite their importance within the energy sector, buildings have not kept pace with technological improvements and particularly the introduction of intelligent features. A primary obstacle in enabling intelligent buildings is their highly distributed and diffuse nature. To address this challenge, a modular approach will be investigated for building design, construction, and operation that would completely transform the building industry. Buildings would be assembled from a set of pre-engineered intelligent modules and commissioned on site in a "plug-and-play" manner much like a "LEGO" set but with added capability of (a) allowing for easy configuration and re-configuration that can be integrated to provide delivery of thermal and visual comfort, ventilation; (b) providing optimized controls in terms of overall occupant satisfaction and energy efficiency and performance monitoring. The primary goal of the research is to develop and demonstrate innovative concepts for distributed intelligence along with a new paradigm for plug-and-play building control that is a necessary precursor in enabling this transformation. To accomplish these tasks, the investigators constitute a multidisciplinary team with expertise from three engineering disciplines, namely Civil (Architectural), Mechanical, Electrical and Computer Engineering. The intellectual merit of this research lies in developing a unified approach that advances the engineering of cyber-physical systems (CPS) for buildings by contributing to the following fields: (a) modeling and identification of building subsystems and integrated systems; (b) multi-agent system networks that enable distributed intelligent monitoring and control of multi-zone buildings; (c) optimal control algorithms for stochastic hybrid systems that can optimize the operation of buildings with mode changes under uncertainty. These contributions will be integrated in simulation and experimental platforms for multi-agent building system networks to validate the developed algorithms and to provide a new CPS-based technological solution to the control and optimization of modular buildings. An initial knowledge/technology base will be provided for scalable, adaptive, robust, and efficient engineering solutions for cyber-enabled building systems that will transform the current building operation practice, enabling the next generation of smart buildings with optimized comfort delivery and energy use. The broader impacts of this project are: (a) Theoretical development of modeling representations, algorithms, and simulation tools that will impact a number of scientific communities, including Civil/Architectural, Mechanical and Computer Engineering, Computer Science, and Operations Research. The proposed new principles for heterogeneous multi-agent system networks, distributed intelligence, and optimal hybrid control algorithms will have impacts in a diverse range of fields outside of building systems such as power systems, transportation systems, robotics, etc.; (b) Integration of the proposed modeling, simulation, and experimental platforms into new teaching modules and experiential learning activities that support the curriculum development in three engineering schools and Purdue?s first year engineering program; (c) Dissemination of research outcomes to the industry to open up a new horizon of business and economy that would enable the growth of green and intelligent buildings; (d) The creation of outreach and engagement initiatives that motivate K-12 teachers and students in STEM learning and research, broaden the participation of underrepresented groups in engineering, and motivate undergraduate students to participate in research related to emerging CPS topics.

This Cyber-Physical Systems project designs and evaluates a foundational information substrate for efficient, agile, model-driven, human-centered building systems. The approach is to develop software-defined buildings, to shatter existing stovepipe architectures, dramatically reduce the effort to add new functions and applications without forklift upgrades, and expand communications and control capabilities beyond a single stand-alone building to enable groups of buildings to behave cooperatively and in cooperation with the energy grid. We investigate how such Software-Defined Buildings can be founded on a flexible, multi-service and open Building Integrated Operating System (BIOS) that allows applications to run reliably in safe, sandboxed environments. It supports sensor and actuator access, access management, metadata, archiving, and discovery, as well as multiple simultaneously executing programs. Building operators retain supervisory management, controlling application separation physically (access different controls), temporally (change controls at different times), informationally (what information leaves the building), and logically (what actions or sequences thereof are allowable). We construct, deploy, and demonstrate the capabilities of a prototype BIOS in the context of university, residential buildings and closely related industrial processes. Making buildings more efficient, while keeping occupants comfortable, productive, and healthy, is critical to our economy and health. Transforming buildings into agile, human centered cyber-physical systems eliminates waste, while allowing them to be a proactive resource on the electric grid with zero emission renewable supplies. And by providing greater value from the same physical plant, the SDB approach can move beyond cost-to-build and cost-to-operate metrics to broader return-on-investment for new extendable future-proof technologies.