Large-scale critical infrastructure systems, including energy and transportation networks, comprise millions of individual elements (human, software and hardware) whose actions may be inconsequential in isolation but profoundly important in aggregate. The focus of this project is on the coordination of these elements via ubiquitous sensing, communications, computation, and control, with an emphasis on the electric grid. The project integrates ideas from economics and behavioral science into frameworks grounded in control theory and power systems. Our central construct is that of a ?resource cluster,? a collection of distributed resources (ex: solar PV, storage, deferrable loads) that can be coordinated to efficiently and reliably offer services (ex: power delivery) in the face of uncertainty (ex: PV output, consumer behavior). Three topic areas form the core of the project: (a) the theoretical foundations for the ?cluster manager? concept and complementary tools to characterize the capabilities of a resource cluster; (b) centralized resource coordination strategies that span multiple time scales via innovations in stochastic optimal control theory; and (c) decentralized coordination strategies based on cluster manager incentives and built upon foundations of non-cooperative dynamic game theory. These innovations will improve the operation of infrastructure systems via a cyber-physical-social approach to the problem of resource allocation in complex infrastructures. By transforming the role of humans from passive resource recipients to active participants in the electric power system, the project will facilitate energy security for the nation, and climate change mitigation. The project will also engage K-12 students through lab-visits and lectures; address the undergraduate demand for power systems training through curricular innovations at the intersection of cyber-systems engineering and physical power systems; and equip graduate students with the multi-disciplinary training in power systems, communications, control, optimization and economics to become leaders in innovation.

The Boolean Microgrid (BM) emulates the Internet by supplying discrete power and discrete data over a network link that follows Boolean logic and is not continuous as in a conventional 60-Hz-ac or dc microgrid. BM is thus a highly integrated cyber-physical system (CPS) that features the convergence of control, communication and the physical plant. BM?s realization poses the following research challenges that we plan to address: a) what is the most efficient, economic, power-dense, and reliable way of integrating the distributed energy sources and loads to the BM, and the BM to the utility grid, using power-electronic interfaces for seamless and on-demand distributed power delivery? b) what is the control-communication mechanism that optimizes BM nodal and network control performances under conditions of varying power generation and load demand and communication-network throughput and reliability? Our unique approaches to address these research challenges will encompass novel mechanisms based on high-frequency-link power conversion, dynamic-pricing based optimal network capacity and resource utilization, event-triggered sampling and communication, and optimal switching-sequence control. BM has the potential to influence next-generation systems including smart grid, vehicular microgrid, electric ships, military microgrid, electric aircraft, telecommunication systems, and residential, commercial, and critical-infrastructure (e.g., hospital) power systems. On the educational front, the proposed project will provide graduate- and post-graduate-level education to four researchers. Further, multiple undergraduate (including minority) students and middle-school students will be provided research/educational opportunities. The results of the research will be integrated into undergraduate and graduate courses at the collaborating universities including a dedicated course on CPS.

The Boolean Microgrid (BM) emulates the Internet by supplying discrete power and discrete data over a network link that follows Boolean logic and is not continuous as in a conventional 60-Hz-ac or dc microgrid. BM is thus a highly integrated cyber-physical system (CPS) that features the convergence of control, communication and the physical plant. BMs realization poses the following research challenges that we plan to address: a) what is the most efficient, economic, power-dense, and reliable way of integrating the distributed energy sources and loads to the BM, and the BM to the utility grid, using power-electronic interfaces for seamless and on-demand distributed power delivery? b) what is the control-communication mechanism that optimizes BM nodal and network control performances under conditions of varying power generation and load demand and communication-network throughput and reliability? Our unique approaches to address these research challenges will encompass novel mechanisms based on high-frequency-link power conversion, dynamic-pricing based optimal network capacity and resource utilization, event-triggered sampling and communication, and optimal switching-sequence control. BM has the potential to influence next-generation systems including smart grid, vehicular microgrid, electric ships, military microgrid, electric aircraft, telecommunication systems, and residential, commercial, and critical-infrastructure (e.g., hospital) power systems. On the educational front, the proposed project will provide graduate- and post-graduate-level education to four researchers. Further, multiple undergraduate (including minority) students and middle-school students will be provided research/educational opportunities. The results of the research will be integrated into undergraduate and graduate courses at the collaborating universities including a dedicated course on CPS.

Traditionally, buildings have been viewed as mere energy consumers; however, with the new power grid infrastructure and distributed energy resources, buildings can not only consume energy, but they can also output energy. As a result, this project removes traditional boundaries between buildings in the same cluster or between the cluster and power grids, transforming individual smart buildings into NetZero building clusters enabled by cyber-support tools. In this research, a synergistic decision framework is established for temporally, spatially distributed building clusters to work as an adaptive and robust system within a smart grid. The framework includes innovative algorithms and tools for building energy modeling, intelligent data fusion, decentralized decisions and adaptive decisions to address theoretical and practical challenges in next-generation building systems. The research develops cyber-physical engineering tools for demand side load management which has been identified as a major challenge by energy industries. It fundamentally transforms the current centralized and uni-directional power distribution business model to a decentralized and multi-directional power sharing and distribution business model, reducing overall energy consumption and allowing for optimal decisions in changing operation environments. Education and outreach efforts include developing novel educational modules disseminated at the K-12 levels and through the ASEE eGFI repository. Further educational impact occurs through integration with multiple undergraduate and graduate courses at each institution, and with community service groups. Impact is also expanded to the broader energy industry and the operation of healthcare delivery and urban transportation systems through our industry collaborations. http://swag.engineering.asu.edu/ Traditionally, buildings have been viewed as mere energy consumers; however, with the new power grid infrastructure and distributed energy resources, buildings can not only consume energy, but they can also output energy. As a result, this project removes traditional boundaries between buildings in the same cluster or between the cluster and power grids, transforming individual smart buildings into NetZero building clusters enabled by cyber-support tools. In this research, a synergistic decision framework is established for temporally, spatially distributed building clusters to work as an adaptive and robust system within a smart grid. The framework includes innovative algorithms and tools for building energy modeling, intelligent data fusion, decentralized decisions and adaptive decisions to address theoretical and practical challenges in next-generation building systems. The research develops cyber-physical engineering tools for demand side load management which has been identified as a major challenge by energy industries. It fundamentally transforms the current centralized and uni-directional power distribution business model to a decentralized and multi-directional power sharing and distribution business model, reducing overall energy consumption and allowing for optimal decisions in changing operation environments. Education and outreach efforts include developing novel educational modules disseminated at the K-12 levels and through the ASEE eGFI repository. Further educational impact occurs through integration with multiple undergraduate and graduate courses at each institution, and with community service groups. Impact is also expanded to the broader energy industry and the operation of healthcare delivery and urban transportation systems through our industry collaborations. http://swag.engineering.asu.edu/ Traditionally, buildings have been viewed as mere energy consumers; however, with the new power grid infrastructure and distributed energy resources, buildings can not only consume energy, but they can also output energy. As a result, this project removes traditional boundaries between buildings in the same cluster or between the cluster and power grids, transforming individual smart buildings into NetZero building clusters enabled by cyber-support tools. In this research, a synergistic decision framework is established for temporally, spatially distributed building clusters to work as an adaptive and robust system within a smart grid. The framework includes innovative algorithms and tools for building energy modeling, intelligent data fusion, decentralized decisions and adaptive decisions to address theoretical and practical challenges in next-generation building systems. The research develops cyber-physical engineering tools for demand side load management which has been identified as a major challenge by energy industries. It fundamentally transforms the current centralized and uni-directional power distribution business model to a decentralized and multi-directional power sharing and distribution business model, reducing overall energy consumption and allowing for optimal decisions in changing operation environments. Education and outreach efforts include developing novel educational modules disseminated at the K-12 levels and through the ASEE eGFI repository. Further educational impact occurs through integration with multiple undergraduate and graduate courses at each institution, and with community service groups. Impact is also expanded to the broader energy industry and the operation of healthcare delivery and urban transportation systems through our industry collaborations.

The objective of this research is to establish a foundational framework for smart grids that enables significant penetration of renewable DERs and facilitates flexible deployments of plug-and-play applications, similar to the way users connect to the Internet. The approach is to view the overall grid management as an adaptive optimizer to iteratively solve a system-wide optimization problem, where networked sensing, control and verification carry out distributed computation tasks to achieve reliability at all levels, particularly component-level, system-level, and application level. Intellectual merit. Under the common theme of reliability guarantees, distributed monitoring and inference algorithms will be developed to perform fault diagnosis and operate resiliently against all hazards. To attain high reliability, a trustworthy middleware will be used to shield the grid system design from the complexities of the underlying software world while providing services to grid applications through message passing and transactions. Further, selective load/generation control using Automatic Generation Control, based on multi-scale state estimation for energy supply and demand, will be carried out to guarantee that the load and generation in the system remain balanced. Broader impact. The envisioned architecture of the smart grid is an outstanding example of the CPS technology. Built on this critical application study, this collaborative effort will pursue a CPS architecture that enables embedding intelligent computation, communication and control mechanisms into physical systems with active and reconfigurable components. Close collaborations between this team and major EMS and SCADA vendors will pave the path for technology transfer via proof-of-concept demonstrations.

The national transmission networks that deliver high voltage electric power underpin our society and are central to the ongoing transformation of the American energy infrastructure. Transmission networks are very large and complicated engineering systems, and "keeping the lights on" as the transformation of the American energy infrastructure proceeds is a fundamental engineering challenge involving both the physical aspects of the equipment and the cyber aspects of the controls, communications, and computers that run the system. The project develops new principles of cyber-physical engineering by focusing on instabilities of electric power networks that can cause blackouts. It proposes novel approaches to analyze these instabilities and to design cyber-physical control methods to monitor, detect, and mitigate them. The controls must perform robustly in the presence of variability and uncertainty in electric generation, loads, communications, and equipment status, and during abnormal states caused by natural faults or malicious attacks. The research produces cyber-physical engineering methodologies that specifically help to mitigate power system blackouts and more generally show the way forward in designing robust cyber-physical systems in environments characterized by rich dynamics and uncertainty. Education and outreach efforts involve students at high school, undergraduate, and graduate levels, as well as dissemination of results to the public and the engineering and applied science communities in industry, government and universities.

This project, investigating active building facades that proactively contribute to energy conservation by changing their opacity and air permeability as a function of environmental and user parameters, promises to contribute strongly to both the cyber and physical sciences. Often energy is wasted when parts of a building are heated or cooled, but are not actually used, or when they are actively cooled if simply opening a window would suffice. The proposed "Self-Organizing Amorphous Facades" (SOAF) consist of a large number of identical cells that can each change their opacity and air permeability, sense light, temperature, and occupancy, and communicate with each other in a distributed collective. For complex cyber physical systems, this promises to provide a novel design methodology that is potentially applicable to a large class of systems and, therefore, will result in foundational knowledge of use to the community at large. This high-risk, high-reward project integrates ideas from computer science and engineering, with a little human physiology and environmental science thrown in, to develop new theoretical foundations for the design, validation, and improvement of coordination strategies for multi-agent robotic systems. The project's intellectual merit lies in novel algorithms that allow one to take advantage of distributed computation to drastically reduce the dimensionality of the data coming from the system, and novel algorithms that turn low-dimensional control data to the system into high-dimensional control signals. In particular, this research focuses on distributed algorithms that can identify regions that share similar spatio-temporal data, distributed algorithms that recognize patterns and gestures in spatio-temporal data sets, and distributed algorithms that automatically derive distributed policies for global control signals on temperature and light. Broader Impacts: The direct impact of this project will be huge potential reduction in the energy footprint of modern buildings by active lighting and ventilation control. A related impact is the introduction of novel ways of using space using truly reconfigurable walls. Due to its interdisciplinary nature spanning computer science and civil engineering together with its positive environment implications, this project is likely to be attractive to students with a broad range of backgrounds and interests. It will lead to educational modules that let students explore energy, heat transfer and solar gains in a building using sensors, wireless technologies, and algorithms, and introduce students to the challenges of complex cyber-physical systems. The PI proposes outreach to women and minorities and suggests a novel mechanism of comic distribution via HowToons.com that will make technical results and environmental impact of CPS accessible to a wide audience.