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 project focuses on the problem of information acquisition, state estimation and control in the context of cyber physical systems. In our underlying model, a (set of) decision maker(s), by controlling a sequence of actions with uncertain outcomes, dynamically refines the belief about stochastically time-varying parameters of interest. These parameters are then used to control the physical system efficiently and robustly. Here the cyber system collects, processes, and acquires information about the underlying physical system of interest, which is used for its control. The proposed work will develop a new theoretical framework for stochastic learning, decision-making, and control in stochastically-varying cyber physical systems. In order to obtain analytical insights into the structure of efficient design, we first consider the case where the actions of the cyber system only affect the estimate of the underlying physical system. This class of problems arises in the context of (distributed) sensing/tracking of a physical system in isolation from cyber system control of the physical system's state. Joint state estimation and control for cyber-physical systems will then be considered. Here the most natural first step is to obtain sufficient conditions and/or special classes of systems where a separated approach to the information acquisition and efficient control is (near) optimal. To demonstrate its utility in practice, our theoretical framework will be applied in the specific context of energy efficient control of data centers and robust control of the smart grid under limited sensing. The intellectual merit of this work will be to develop a theoretical framework for the design of cyber-physical systems including information acquisition, state estimation, and control. In addition, separation theorems for the optimality of separate state estimation and control will be explored. In terms of broader impacts, significant performance improvement of control systems closed over communication networks will impact a wide range of applications for societal benefit, including smart buildings, intelligent transportation systems, energy-efficient data centers, and the future smart-grid. The PIs plan to disseminate the research results widely through conferences and journals, as well as by organizing specialized workshops and conference sessions related to cyber physical systems. The proposed project will train Ph.D. students as well as enrich the curriculum taught by the PIs in communications, stochastic control, and networks. The PIs have a strong track record in diversity and outreach activities, which for this project will include exposure and involvement of high school and undergraduate students, including under-represented minorities and women.

Reliable operation of cyber-physical systems (CPS) of societal importance such as Smart Electric Grids is critical for the seamless functioning of a vibrant economy. Sustained power outages can lead to major disruptions over large areas costing millions of dollars. Efficient computational techniques and tools that curtail such systematic failures by performing fault diagnosis and prognostics are therefore necessary. The Smart Electric Grid is a CPS: it consists of networks of physical components (including generation, transmission, and distribution facilities) interfaced with cyber components (such as intelligent sensors, communication networks, and control software). This grant provides funding to develop new methods to build models for the smart grid representing the failure dependencies in the physical and cyber components. The models will be used to build an integrated system-wide solution for diagnosing faults and predicting future failure propagations that can account for existing protection mechanisms. The original contribution of this work will be in the integrated modeling of failures on multiple levels in a large distributed cyber-physical system and the development of novel, hierarchical, robust, online algorithms for diagnostics and prognostics. If successful, the model-based fault diagnostics and prognostics techniques will improve the effectiveness of isolating failures in large systems by identifying impending failure propagations and determining the time to critical failures that will increase system reliability and reduce the losses accrued due to failures. This work will bridge the gap between fault management approaches used in computer science and power engineering that are needed as the grid becomes smarter, more complex, and more data intensive. Outcomes of this project will include modeling and run-time software prototypes, research publications, and experimental results in collaborations with industry partners that will be made available to the scientific community.

Reliable operation of cyber-physical systems (CPS) of societal importance such as Smart Electric Grids is critical for the seamless functioning of a vibrant economy. Sustained power outages can lead to major disruptions over large areas costing millions of dollars. Efficient computational techniques and tools that curtail such systematic failures by performing fault diagnosis and prognostics are therefore necessary. The Smart Electric Grid is a CPS: it consists of networks of physical components (including generation, transmission, and distribution facilities) interfaced with cyber components (such as intelligent sensors, communication networks, and control software). This grant provides funding to develop new methods to build models for the smart grid representing the failure dependencies in the physical and cyber components. The models will be used to build an integrated system-wide solution for diagnosing faults and predicting future failure propagations that can account for existing protection mechanisms. The original contribution of this work will be in the integrated modeling of failures on multiple levels in a large distributed cyber-physical system and the development of novel, hierarchical, robust, online algorithms for diagnostics and prognostics. If successful, the model-based fault diagnostics and prognostics techniques will improve the effectiveness of isolating failures in large systems by identifying impending failure propagations and determining the time to critical failures that will increase system reliability and reduce the losses accrued due to failures. This work will bridge the gap between fault management approaches used in computer science and power engineering that are needed as the grid becomes smarter, more complex, and more data intensive. Outcomes of this project will include modeling and run-time software prototypes, research publications, and experimental results in collaborations with industry partners that will be made available to the scientific community.

The objective of this proposal is to develop a distributed algorithmic framework, supported by a highly fault-tolerant software system, for executing critical transmission-level operations of the North American power grid using gigantic volumes of Synchrophasor data. As the number of Phasor Measurement Units (PMU) increases to more than thousands in the next 4-5 years, it is rather intuitive that the current state-of-the-art centralized communication and information processing architecture of Wide-Area Measurement System (WAMS) will no longer be sustainable under such data-explosion, and a completely distributed cyber-physical architecture will need to be developed. The North American Synchrophasor Initiative (NASPI) is currently addressing this architectural aspect by developing new communication and computing protocols through NASPI-net and Phasor Gateway. However, very little attention has been paid so far to perhaps the most critical consequence of this envisioned distributed architecture "namely", distributed algorithms, and their relevant middleware. Our primary task, therefore, will be to develop parallel computational methods for solving real-time wide-area monitoring and control problems with analytical investigation of their stability, convergence and robustness properties, followed by their implementation and testing against extraneous malicious attacks using our WAMS-RTDS testbed at NC State. In particular, we will address three critical research problems "namely" distributed wide-area oscillation monitoring, transient stability assessment, and voltage stability monitoring. The intellectual merit of this research will be in establishing an extremely timely application area of the PMU technology through its integration with distributed computing and optimal control. It will illustrate how ideas from advanced ideas from numerical methods and distributed optimization can be combined into power system monitoring and control applications, and how they can be implemented via fault-tolerant computing to maintain grid stability in face of catastrophic cyber and physical disturbances. The broader impact of this project will be in providing a much-needed application of CPS engineering to advance emerging research on PMU-integrated next-generation smart grids. Research results will be broadcast through journal publications, jointly organized graduate courses between NC State and University of Illinois Urbana Champagne, conference tutorials and workshops. Undergraduate research for minority engineering students will be promoted via the FREEDM Systems Center, summer internships via Information Trust Institute (UIUC) and RENCI, and middle/high-school student mentoring through the NCSU Science House program.

The objective of this proposal is to develop a distributed algorithmic framework, supported by a highly fault-tolerant software system, for executing critical transmission-level operations of the North American power grid using gigantic volumes of Synchrophasor data. As the number of Phasor Measurement Units (PMU) increases to more than thousands in the next 4-5 years, it is rather intuitive that the current state-of-the-art centralized communication and information processing architecture of Wide-Area Measurement System (WAMS) will no longer be sustainable under such data-explosion, and a completely distributed cyber-physical architecture will need to be developed. The North American Synchrophasor Initiative (NASPI) is currently addressing this architectural aspect by developing new communication and computing protocols through NASPI-net and Phasor Gateway. However, very little attention has been paid so far to perhaps the most critical consequence of this envisioned distributed architecture "namely", distributed algorithms, and their relevant middleware. Our primary task, therefore, will be to develop parallel computational methods for solving real-time wide-area monitoring and control problems with analytical investigation of their stability, convergence and robustness properties, followed by their implementation and testing against extraneous malicious attacks using our WAMS-RTDS testbed at NC State. In particular, we will address three critical research problems "namely" distributed wide-area oscillation monitoring, transient stability assessment, and voltage stability monitoring. The intellectual merit of this research will be in establishing an extremely timely application area of the PMU technology through its integration with distributed computing and optimal control. It will illustrate how ideas from advanced ideas from numerical methods and distributed optimization can be combined into power system monitoring and control applications, and how they can be implemented via fault-tolerant computing to maintain grid stability in face of catastrophic cyber and physical disturbances. The broader impact of this project will be in providing a much-needed application of CPS engineering to advance emerging research on PMU-integrated next-generation smart grids. Research results will be broadcast through journal publications, jointly organized graduate courses between NC State and University of Illinois Urbana Champagne, conference tutorials and workshops. Undergraduate research for minority engineering students will be promoted via the FREEDM Systems Center, summer internships via Information Trust Institute (UIUC) and RENCI, and middle/high-school student mentoring through the NCSU Science House program.

The objective of this proposal is to develop a distributed algorithmic framework, supported by a highly fault-tolerant software system, for executing critical transmission-level operations of the North American power grid using gigantic volumes of Synchrophasor data. As the number of Phasor Measurement Units (PMU) increases to more than thousands in the next 4-5 years, it is rather intuitive that the current state-of-the-art centralized communication and information processing architecture of Wide-Area Measurement System (WAMS) will no longer be sustainable under such data-explosion, and a completely distributed cyber-physical architecture will need to be developed. The North American Synchrophasor Initiative (NASPI) is currently addressing this architectural aspect by developing new communication and computing protocols through NASPI-net and Phasor Gateway. However, very little attention has been paid so far to perhaps the most critical consequence of this envisioned distributed architecture "namely", distributed algorithms, and their relevant middleware. Our primary task, therefore, will be to develop parallel computational methods for solving real-time wide-area monitoring and control problems with analytical investigation of their stability, convergence and robustness properties, followed by their implementation and testing against extraneous malicious attacks using our WAMS-RTDS testbed at NC State. In particular, we will address three critical research problems "namely" distributed wide-area oscillation monitoring, transient stability assessment, and voltage stability monitoring. The intellectual merit of this research will be in establishing an extremely timely application area of the PMU technology through its integration with distributed computing and optimal control. It will illustrate how ideas from advanced ideas from numerical methods and distributed optimization can be combined into power system monitoring and control applications, and how they can be implemented via fault-tolerant computing to maintain grid stability in face of catastrophic cyber and physical disturbances. The broader impact of this project will be in providing a much-needed application of CPS engineering to advance emerging research on PMU-integrated next-generation smart grids. Research results will be broadcast through journal publications, jointly organized graduate courses between NC State and University of Illinois Urbana Champagne, conference tutorials and workshops. Undergraduate research for minority engineering students will be promoted via the FREEDM Systems Center, summer internships via Information Trust Institute (UIUC) and RENCI, and middle/high-school student mentoring through the NCSU Science House program.

Reliable operation of cyber-physical systems (CPS) of societal importance such as Smart Electric Grids is critical for the seamless functioning of a vibrant economy. Sustained power outages can lead to major disruptions over large areas costing millions of dollars. Efficient computational techniques and tools that curtail such systematic failures by performing fault diagnosis and prognostics are therefore necessary. The Smart Electric Grid is a CPS: it consists of networks of physical components (including generation, transmission, and distribution facilities) interfaced with cyber components (such as intelligent sensors, communication networks, and control software). This grant provides funding to develop new methods to build models for the smart grid representing the failure dependencies in the physical and cyber components. The models will be used to build an integrated system-wide solution for diagnosing faults and predicting future failure propagations that can account for existing protection mechanisms. The original contribution of this work will be in the integrated modeling of failures on multiple levels in a large distributed cyber-physical system and the development of novel, hierarchical, robust, online algorithms for diagnostics and prognostics. If successful, the model-based fault diagnostics and prognostics techniques will improve the effectiveness of isolating failures in large systems by identifying impending failure propagations and determining the time to critical failures that will increase system reliability and reduce the losses accrued due to failures. This work will bridge the gap between fault management approaches used in computer science and power engineering that are needed as the grid becomes smarter, more complex, and more data intensive. Outcomes of this project will include modeling and run-time software prototypes, research publications, and experimental results in collaborations with industry partners that will be made available to the scientific community.

The electric power grid is a national critical infrastructure that is increasing vulnerable to malicious physical and cyber attacks. As a result, detailed data describing grid topology and components is considered highly sensitive information that can be shared only under strict non-disclosure agreements. There is also increasing need to foster cooperation among the growing number of participants in microgrid-enabled electric marketplace. However, to maintain their economic competitiveness, the market participants are not inclined to share sensitive information about their grid with other participants. Motivated by this need for increased cyber-physical security and economic confidentiality, the project is developing techniques to obfuscate sensitive design information in power system models without jeopardizing the quality of the solutions obtained from such models. Specifically, solution approaches have been developed to hide sensitive structural information in Direct Current (DC) Optimal Power Flow models. These approaches are currently being extended to Alternating Current (AC) Optimal Power Flow models. The project is also developing secure multi-party methods where the market participants collectively optimize the grid operation while only sharing encrypted private sensitive information. Finally, the project is incorporating secure market operations in jointly solving the Optimal Power Dispatch problem without revealing sensitive private information from each participant to other participants. The techniques developed in this project have the potential to broadly impact areas beyond power systems. The general principles developed in the project can be used to mask sensitive information in many problems that can be formulated as a linear or non-linear programming optimization.

This project designs algorithms for the integration of plug-in hybrid electric vehicles (PEVs) into the power grid. Specifically, the project will formulate and solve optimization problems critical to various entities in the PEV ecosystem -- PEV owners, commercial charging station owners, aggregators, and distribution companies -- at the distribution / retail level. Charging at both commercial charging stations and at residences will be considered, for both the case when PEVs only function as loads, and the case when they can also function as sources, equipped with vehicle-to-home (V2H) or vehicle-to-grid (V2G) energy reinjection capability. The focus of the project is on distributed decision making by various individual players to achieve analytical system-level performance guarantees. Electrification of the transportation market offers revenue growth for utility companies and automobile manufacturers, lower operational costs for consumers, and benefits to the environment. By addressing problems that will arise as PEVs impose extra load on the grid, and by solving challenges that currently impede the use of PEVs as distributed storage resources, this research will directly impact the society. The design principles gained will also be applicable to other cyber-physical infrastructural systems. A close collaboration with industrial partners will ground the research in real problems and ensure quick dissemination of results to the marketplace. A strong educational component will integrate the proposed research into the classroom to allow better training of both undergraduate and graduate students. The details of the project will be provided at http://ee.nd.edu/faculty/vgupta/research/funding/cps_pev.html