The wide-area measurement systems technology using Phasor Measurement Units (PMUs) has been regarded as the key to guaranteeing stability, reliability, state estimation, and control of next-generation power systems. However, with the exponentially increasing number of PMUs, and the resulting explosion in data volume, the design and deployment of an efficient wide-area communication and computing infrastructure is evolving as one of the greatest challenges to the power system and IT communities. The goal of this NSF CPS project is to address this challenge, and construct a massively deployable cyber-physical architecture for wide-area control that is fast, resilient and cost-optimal (FRESCO). The FRESCO grid will consist of a suite of optimal control algorithms for damping oscillations in power flows and voltages, implemented on top of a cost-effective and cyber-secure distributed computing infrastructure connected by high-speed wide-area networks that are dynamically programmable and reconfigurable. The value of constructing FRESCO is twofold (1) If a US-wide communication network capable of transporting gigabit volumes of PMU data for wide-area control indeed needs to be implemented over the next five years then power system operators must have a clear sense of how various forms of delays, packet losses, and security threats affect the stability of these control loops. (2) Moreover, such wide-area communication must be made economically feasible and sustainable via joint decision-making processes between participating utility companies, and testing how controls can play a potential role in facilitating such economics. Currently, there is very limited insight into how the PMU data transport protocols may lead to a variety of such delay patterns, or dictate the economic investments. FRESCO will answer all of these questions, starting from small prototypical grid models to those with tens of thousands of buses. Our eventual goal will be to make FRESCO fully open-source for Transition to Practice (TTP). We will work with two local software companies in Raleigh, namely Green Energy Corporation and Real-Time Innovations, Inc. to develop a scalable, secure middleware using Data-Distribution Service (DDS) technology. Thus, within the scope of the project, we also expect to enrich the state-of-the-art cloud computing and networking technologies with new control and management functions. From a technical perspective, FRESCO will answer three main research questions. First, can wide-area controllers be co-designed in sync with communication delays to make the closed-loop system resilient and delay-aware, rather than just delay-tolerant This is particularly important, as PMU data, in most practical scenarios, will have to be transported over a shared resource, sharing bandwidth with other ongoing applications, giving rise to not only transport delays, but also significant delays due to queuing and routing. Advanced ideas of arbitrated network control designs will be used to address this problem. The second question we address is for cost. Given that there are several participants in this wide-area control, how much is each participant willing to pay in sharing the network cost with others for the sake of supporting a system-wide control objective compared to its current practice of opting for selfish feedback control only Ideas from cooperative game theory will be used to investigate this problem. The final question addresses security how can one develop a scientific methodology to assess risks, and mitigate security attacks in wide-area control? Statistical and structural analysis of attack defense modes using Bayesian and Markov models, game theory, and discrete-event simulation will be used to address this issue. Experimental demos will be carried out using the DETER-WAMS network, showcasing the importance of cyber-innovation for the sustainability of energy infrastructures. Research results will be broadcast through journal publications, and jointly organized graduate courses between NCSU, MIT and USC.

The wide-area measurement systems technology using Phasor Measurement Units (PMUs) has been regarded as the key to guaranteeing stability, reliability, state estimation, and control of next-generation power systems. However, with the exponentially increasing number of PMUs, and the resulting explosion in data volume, the design and deployment of an efficient wide-area communication and computing infrastructure is evolving as one of the greatest challenges to the power system and IT communities. The goal of this NSF CPS project is to address this challenge, and construct a massively deployable cyber-physical architecture for wide-area control that is fast, resilient and cost-optimal (FRESCO). The FRESCO grid will consist of a suite of optimal control algorithms for damping oscillations in power flows and voltages, implemented on top of a cost-effective and cyber-secure distributed computing infrastructure connected by high-speed wide-area networks that are dynamically programmable and reconfigurable. The value of constructing FRESCO is twofold (1) If a US-wide communication network capable of transporting gigabit volumes of PMU data for wide-area control indeed needs to be implemented over the next five years then power system operators must have a clear sense of how various forms of delays, packet losses, and security threats affect the stability of these control loops. (2) Moreover, such wide-area communication must be made economically feasible and sustainable via joint decision-making processes between participating utility companies, and testing how controls can play a potential role in facilitating such economics. Currently, there is very limited insight into how the PMU data transport protocols may lead to a variety of such delay patterns, or dictate the economic investments. FRESCO will answer all of these questions, starting from small prototypical grid models to those with tens of thousands of buses. Our eventual goal will be to make FRESCO fully open-source for Transition to Practice (TTP). We will work with two local software companies in Raleigh, namely Green Energy Corporation and Real-Time Innovations, Inc. to develop a scalable, secure middleware using Data-Distribution Service (DDS) technology. Thus, within the scope of the project, we also expect to enrich the state-of-the-art cloud computing and networking technologies with new control and management functions. From a technical perspective, FRESCO will answer three main research questions. First, can wide-area controllers be co-designed in sync with communication delays to make the closed-loop system resilient and delay-aware, rather than just delay-tolerant This is particularly important, as PMU data, in most practical scenarios, will have to be transported over a shared resource, sharing bandwidth with other ongoing applications, giving rise to not only transport delays, but also significant delays due to queuing and routing. Advanced ideas of arbitrated network control designs will be used to address this problem. The second question we address is for cost. Given that there are several participants in this wide-area control, how much is each participant willing to pay in sharing the network cost with others for the sake of supporting a system-wide control objective compared to its current practice of opting for selfish feedback control only Ideas from cooperative game theory will be used to investigate this problem. The final question addresses security how can one develop a scientific methodology to assess risks, and mitigate security attacks in wide-area control? Statistical and structural analysis of attack defense modes using Bayesian and Markov models, game theory, and discrete-event simulation will be used to address this issue. Experimental demos will be carried out using the DETER-WAMS network, showcasing the importance of cyber-innovation for the sustainability of energy infrastructures. Research results will be broadcast through journal publications, and jointly organized graduate courses between NCSU, MIT and USC.

Cyber-physical additive layer manufacturing, e.g., 3D printing, has become a promising technology for providing cost, time, and space effective solution by reducing the gap between designers and manufacturers. However, the concern for the protection of intellectual property is arising in conjunction with the capabilities of supporting massive innovative designs and rapid prototyping. Intellectual property in the additive layer manufacturing system consists of: i) geometric design of an object; ii) attributes of an object; iii) process information; and iv) machine information. This Early-concept Grant for Exploratory Research (EAGER) project seeks to develop defense mechanisms for detecting malware and counterfeit articles using a variety of signals that are observed during the manufacturing process including acoustic, temperature, power, and others. The project is an EAGER because both the uniqueness of the observed signal signatures, and their utilization in securing the manufacturing process are high risk with potential for high reward in thwarting attacks. This project will demonstrate that during the life-cycle of the additive layer manufacturing system, the intellectual property information contained in the cyber domain can be recovered/reconstructed through attacks occurring during the manufacturing process in the physical domain through various non-intrusive techniques. It will then focus on creating both machine-dependent and machine-independent defense mechanisms for avoiding such an attack. This project will significantly impact US competitiveness over technology-oriented manufacturing. The attack model will provide feedback to 3D printer manufacturers and CAD tool designers to build defenses against these new types of attack. Moreover, it will have a significant societal impact to the explosively growing maker and crowd-sourcing community in protecting their intellectual property. In addition, the project's approach can be used in other manufacturing systems, e.g., CNC machines, manufacturing robots, etc. This is possibly the very first approach to create defense for additive layer manufacturing mechanisms against such attacks occurring in the physical domain to get access to information of the cyber domain. This project has three specific objectives: 1) It will demonstrate a proof of concept by presenting a novel attack model constructed using a combination of machine learning, signal processing, and pattern recognition techniques that utilize the side-channel information (power, temperature, acoustic, electromagnetic emission) obtained during the manufacturing process. 2) It will develop a machine-specific defense mechanism against the attack model for the 3D printer. New techniques to add additional physical process encryption, e.g. adding extra information to the G-code to obfuscate the printing process from the attack model between the G-code and the physical manufacturing process, will be demonstrated. 3) It will create a new security-aware 3D-printing algorithm for the machine-independent CAD tools that can protect against such side channel attacks. The 3D-printing algorithm will slice the STL and generate layer description language (e.g. G-code) randomly so that for the same 3D object, different instructions will be sent to the 3D printer and eventually different physical features will be extracted by the attackers.