ENERGY RESILIENCE IMPACT OF SUPPLY CHAIN NETWORK DISRUPTION TO MILITARY MICROGRIDS

The ability to provide uninterrupted power to military installations is paramount in executing a country's national defense strategy. Microgrid architectures increase installation energy resilience through redundant local generation sources and the capability for grid independence. However, deliberate attacks from near-peer competitors can disrupt the associated supply chain network, thereby affecting mission-critical loads. Utilizing an integrated discrete-time Markov chain and dynamic Bayesian network approach, we investigate disruption propagation throughout a supply chain network and quantify its mission impact on an islanded microgrid. We propose a novel methodology and an associated metric we term "energy resilience impact" to identify and address supply-chain disruption risks to energy security. A case study of a fictional military installation is presented to demonstrate how installation energy managers can adopt this methodology for the design and improvement of military microgrids.Outstanding ThesisLieutenant, United States NavyApproved for public release. Distribution is unlimited

Risk Management Decision Making for Security and Trust in Hardware Supply Chains

Modern cyber-physical systems are enabled by electronic hardware and embedded systems. The security of these sub-components is a concern during the design and operational phases of cyber-physical system life cycles. Compromised electronics can result in mission-critical failures, unauthorized access, and other severe consequences. As systems become more complex and feature greater connectivity, system owners must make decisions regarding how to mitigate risks and ensure resilience and trust. This paper provides an overview of research efforts related to assessing and managing risks, resilience, and trust with an emphasis on electronic hardware and embedded systems. The research takes a decision-oriented perspective, drawing from the perspectives of scenario planning and portfolio analysis, and describes examples related to the risk-based prioritization of cyber assets in large-scale systems

Identifying industry 5.0 contributions to sustainable development: A strategy roadmap for delivering sustainability values

Scholars believe that the newly introduced Industry 5.0 has the potential to move beyond the profit-centered productivity of Industry 4.0 and to promote sustainable development goals such as human-centricity, socio-environmental sustainability, and resilience. However, little has been done to understand how this ill-defined phenomenon may deliver its indented sustainability values despite these speculative promises. To address this knowledge gap, the present study developed a strategy roadmap that explains the mechanism by which Industry 5.0 delivers its intended sustainable development functions. The study first developed and introduced the Industry 5.0 reference model that describes the technical and functional properties of this phenomenon. The study further conducted a content-centric synthesis of the literature and identified the sustainable development functions of Industry 5.0. Next, the interpretive structural modeling (ISM) technique was employed to identify the sequential relationships among the functions and construct the Industry 5.0-enabled model of sustainable development. The ISM involved collecting the opinions of 11 Industry 5.0 experts through expert panel meetings. Results revealed that Industry 5.0 delivers sustainable development values through 16 functions. Circular intelligent products, employee technical assistance, intelligent automation, open sustainable innovation, renewable integration, and supply chain adaptability are examples of the functions identified. These functions are highly interrelated and should be developed in a specific order so that the synergies and complementarities among them would maximize the sustainable development value gains. The roadmap to Industry 5.0-driven sustainability developed in this study is expected to provide a better understanding of ways Industry 5.0 can contribute to sustainable development, explaining how the development of its functions should be managed to maximize their synergies and contribution to the intended sustainability values. The study also highlights important avenues for future research, emphasizing the potential enablers of Industry 5.0 development, such as Government 5.0 or Corporate Governance 5.0

Investigation of PESTEL factors driving change in capital project organizations

In a volatile, uncertain, complex, and ambiguous environment, organizational change has been a central concern for capital project organizations, that continue to suffer from poor project performance in a growing industry. As such, capital project organizations must understand the changing environment and the factors driving change within their organizations to remain successful in a changing environment and adapt to change. To help the capital projects industry achieve successful organizational change efforts, this paper aims to 1) identify the external factors that are pushing capital project organizations to change and 2) investigate whether these factors impact organizations differently. To achieve the desired objective, a total of 22 PESTEL (political, economic, social, technological, environmental, and legal) factors were identified and validated with a group of 14 subject matter experts and defined via the context of literature. Then, the factors were evaluated via an online survey to understand whether they impact organizations differently based on their age maturity (including contemporary, transitional, and legacy organizations) and type of work (including owners, contractors, and service providers). Findings from this study can provide capital project practitioners and researchers with valuable insights needed to understand the external factors shaping change within the industry

Cognitive Hyperconnected Digital Transformation

Cognitive Hyperconnected Digital Transformation provides an overview of the current Internet of Things (IoT) landscape, ranging from research, innovation and development priorities to enabling technologies in a global context. It is intended as a standalone book in a series that covers the Internet of Things activities of the IERC-Internet of Things European Research Cluster, including both research and technological innovation, validation and deployment. The book builds on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT-EPI) and the IoT European Large-Scale Pilots Programme, presenting global views and state-of-the-art results regarding the challenges facing IoT research, innovation, development and deployment in the next years. Hyperconnected environments integrating industrial/business/consumer IoT technologies and applications require new IoT open systems architectures integrated with network architecture (a knowledge-centric network for IoT), IoT system design and open, horizontal and interoperable platforms managing things that are digital, automated and connected and that function in real-time with remote access and control based on Internet-enabled tools. The IoT is bridging the physical world with the virtual world by combining augmented reality (AR), virtual reality (VR), machine learning and artificial intelligence (AI) to support the physical-digital integrations in the Internet of mobile things based on sensors/actuators, communication, analytics technologies, cyber-physical systems, software, cognitive systems and IoT platforms with multiple functionalities. These IoT systems have the potential to understand, learn, predict, adapt and operate autonomously. They can change future behaviour, while the combination of extensive parallel processing power, advanced algorithms and data sets feed the cognitive algorithms that allow the IoT systems to develop new services and propose new solutions. IoT technologies are moving into the industrial space and enhancing traditional industrial platforms with solutions that break free of device-, operating system- and protocol-dependency. Secure edge computing solutions replace local networks, web services replace software, and devices with networked programmable logic controllers (NPLCs) based on Internet protocols replace devices that use proprietary protocols. Information captured by edge devices on the factory floor is secure and accessible from any location in real time, opening the communication gateway both vertically (connecting machines across the factory and enabling the instant availability of data to stakeholders within operational silos) and horizontally (with one framework for the entire supply chain, across departments, business units, global factory locations and other markets). End-to-end security and privacy solutions in IoT space require agile, context-aware and scalable components with mechanisms that are both fluid and adaptive. The convergence of IT (information technology) and OT (operational technology) makes security and privacy by default a new important element where security is addressed at the architecture level, across applications and domains, using multi-layered distributed security measures. Blockchain is transforming industry operating models by adding trust to untrusted environments, providing distributed security mechanisms and transparent access to the information in the chain. Digital technology platforms are evolving, with IoT platforms integrating complex information systems, customer experience, analytics and intelligence to enable new capabilities and business models for digital business

Demand-Response in Smart Buildings

This book represents the Special Issue of Energies, entitled “Demand-Response in Smart Buildings”, that was published in the section “Energy and Buildings”. This Special Issue is a collection of original scientific contributions and review papers that deal with smart buildings and communities. Demand response (DR) offers the capability to apply changes in the energy usage of consumers—from their normal consumption patterns—in response to changes in energy pricing over time. This leads to a lower energy demand during peak hours or during periods when an electricity grid’s reliability is put at risk. Therefore, demand response is a reduction in demand designed to reduce peak load or avoid system emergencies. Hence, demand response can be more cost-effective than adding generation capabilities to meet the peak and/or occasional demand spikes. The underlying objective of DR is to actively engage customers in modifying their consumption in response to pricing signals. Demand response is expected to increase energy market efficiency and the security of supply, which will ultimately benefit customers by way of options for managing their electricity costs leading to reduced environmental impact

Occupant-Centric Modeling and Control for Low-Carbon and Resilient Communities

Global climate change and resulting frequent extreme weather events have highlighted the significance of energy sustainability and resilience. Communities, which refer to a group of buildings located geographically together, are important units for energy generation and consumption. Hence, the research of community energy sustainability and resilience has drawn much attention during the past decades. However, there remain many challenges surrounding community energy modeling and control to achieve the low-carbon and resilient goals. First, few tools are readily available for community-scale dynamic modeling and control-based studies. To address this gap, a community emulator was developed, which was designed to be hierarchical, scalable, and suitable for various applications. Data-driven stochastic building occupancy prediction was integrated into the emulator using logistic regression methods. Based on this work, we publicly released a library for net-zero energy community modeling using the object-oriented equation-based modeling language Modelica. Second, building load control informed by real-time carbon emission signals is underdeveloped as utility price-driven control has so far been dominant. To better facilitate community energy sustainability through decarbonization, we proposed four rule-based carbon emission responsive building control algorithms to reduce the annual carbon emissions through thermostatically controllable loads. The impact of carbon net-metering, as well as the evolvement of the future energy generation mix, is analyzed on top of both momentary and predictive rules. Based on the simulation results, the average annual household carbon emissions are decreased by 6.0% to 20.5% compared to the baseline. The average annual energy consumption is increased by less than 6.7% due to more clean hours over the year. The annual energy cost change lies between -4.1% and 3.4% on top of the baseline. Third, the enhancement of community resilience in an islanded mode through optimal operation strategies is often faced with computational challenges given the large number of controllable loads. To tackle this, we proposed a two-layer model predictive control-based resource allocation and load scheduling framework for community resilience enhancement. Within this framework, the community operator layer optimally allocates the available PV generation to each building, while the building agent layer optimally schedules controllable loads to minimize the unserved load ratio while maintaining thermal comfort. We found that the allocation process is mostly constrained by the building load flexibility. More specifically, buildings with less load flexibility tend to be allocated more PV generation than other buildings. Further, we identified the competitive relationship between the objectives of minimizing unserved load ratio and maximize comfort. Therefore, it is necessary for the building agent to have multi-objective optimization. Finally, to account for the uncertainties of occupant behavior and its impact on resilient community load scheduling, we developed a preference-aware scheduler for resilient communities. Stochastic occupant thermostat-changing behavior models were introduced into the deterministic load scheduling framework as a source of uncertainty. KRIs such as the unserved load ratio, the required battery size, and the unmet thermal preference hours were adopted to quantify the impacts. Uncertainties from occupants&rsquo; thermal preferences and their impact on load scheduling are then studied and addressed through chance constraints. Generally, the proposed controller performs better in terms of the unmet thermal preference hours and the battery sizes compared to the deterministic controller.</p

Cognitive Hyperconnected Digital Transformation

Cognitive Hyperconnected Digital Transformation provides an overview of the current Internet of Things (IoT) landscape, ranging from research, innovation and development priorities to enabling technologies in a global context. It is intended as a standalone book in a series that covers the Internet of Things activities of the IERC-Internet of Things European Research Cluster, including both research and technological innovation, validation and deployment. The book builds on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT-EPI) and the IoT European Large-Scale Pilots Programme, presenting global views and state-of-the-art results regarding the challenges facing IoT research, innovation, development and deployment in the next years. Hyperconnected environments integrating industrial/business/consumer IoT technologies and applications require new IoT open systems architectures integrated with network architecture (a knowledge-centric network for IoT), IoT system design and open, horizontal and interoperable platforms managing things that are digital, automated and connected and that function in real-time with remote access and control based on Internet-enabled tools. The IoT is bridging the physical world with the virtual world by combining augmented reality (AR), virtual reality (VR), machine learning and artificial intelligence (AI) to support the physical-digital integrations in the Internet of mobile things based on sensors/actuators, communication, analytics technologies, cyber-physical systems, software, cognitive systems and IoT platforms with multiple functionalities. These IoT systems have the potential to understand, learn, predict, adapt and operate autonomously. They can change future behaviour, while the combination of extensive parallel processing power, advanced algorithms and data sets feed the cognitive algorithms that allow the IoT systems to develop new services and propose new solutions. IoT technologies are moving into the industrial space and enhancing traditional industrial platforms with solutions that break free of device-, operating system- and protocol-dependency. Secure edge computing solutions replace local networks, web services replace software, and devices with networked programmable logic controllers (NPLCs) based on Internet protocols replace devices that use proprietary protocols. Information captured by edge devices on the factory floor is secure and accessible from any location in real time, opening the communication gateway both vertically (connecting machines across the factory and enabling the instant availability of data to stakeholders within operational silos) and horizontally (with one framework for the entire supply chain, across departments, business units, global factory locations and other markets). End-to-end security and privacy solutions in IoT space require agile, context-aware and scalable components with mechanisms that are both fluid and adaptive. The convergence of IT (information technology) and OT (operational technology) makes security and privacy by default a new important element where security is addressed at the architecture level, across applications and domains, using multi-layered distributed security measures. Blockchain is transforming industry operating models by adding trust to untrusted environments, providing distributed security mechanisms and transparent access to the information in the chain. Digital technology platforms are evolving, with IoT platforms integrating complex information systems, customer experience, analytics and intelligence to enable new capabilities and business models for digital business