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1. Cyber Attack and Defense for Smart Inverters in a Distribution System

   Sun, C. C. ; Zhu, R. ; Liu, C. C. ( June 2019 , CIGRE D2 Colloquium, Helsinki, Finland)

   In this paper, a signature-based Intrusion Detection System (IDS) is developed to detect cyber intrusions of a distribution system with a high level penetration of solar energy. To identify cyberattack events, an attack table is constructed based on the Temporal Failure Propagation Graph (TFPG) technique. It includes the information of potential cyberattack patterns in terms of attack types and time sequence of anomaly events. Once the detected anomaly events are matched with any of the predefined attack patterns, it is judged to be a cyberattack. Since the attack patterns are distinguishable from other system failures, it reduces the false positive rate. To study the impact of cyberattacks on solar devices and validate the performance of the proposed IDS, a realistic Cyber-Physical System (CPS) simulation environment available at Virginia Tech (VT) is used to develop an interconnection between the cyber and power system models. The CPS model demonstrates how communication system anomalies can impact the physical system. The results of two example cyberattack test cases are obtained with the IEEE 13 node test feeder system and the power system simulator, DIgSILENT PowerFactory. 

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2. Cyber Attack and Defense for Smart Inverters in a Distribution System

   Sun, C. C. ; Zhu, R. ; Liu, C. C. ( June 2019 , CIGRE Study Committee D2 Colloquium, Helsinki, Finland)

   The fast-growing installation of solar PVs has a significant impact on the operation of distribution systems. Grid-tied solar inverters provide reactive power capability to support the voltage profile in a distribution system. In comparison with traditional inverters, smart inverters have the capability of real time remote control through digital communication interfaces. However, cyberattack has become a major threat with the deployment of Information and Communications Technology (ICT) in a smart grid. The past cyberattack incidents have demonstrated how attackers can sabotage a power grid through digital communication systems. In the worst case, numerous electricity consumers can experience a major and extended power outage. Unfortunately, tracking techniques are not efficient for today’s advanced communication networks. Therefore, a reliable cyber protection system is a necessary defense tool for the power grid. In this paper, a signature-based Intrusion Detection System (IDS) is developed to detect cyber intrusions of a distribution system with a high level penetration of solar energy. To identify cyberattack events, an attack table is constructed based on the Temporal Failure Propagation Graph (TFPG) technique. It includes the information of potential cyberattack patterns in terms of attack types and time sequence of anomaly events. Once the detected anomaly events are matched with any of the predefined attack patterns, it is judged to be a cyberattack. Since the attack patterns are distinguishable from other system failures, it reduces the false positive rate. To study the impact of cyberattacks on solar devices and validate the performance of the proposed IDS, a realistic Cyber-Physical System (CPS) simulation environment available at Virginia Tech (VT) is used to develop an interconnection between the cyber and power system models. The CPS model demonstrates how communication system anomalies can impact the physical system. The results of two example cyberattack test cases are obtained with the IEEE 13 node test feeder system and the power system simulator, DIgSILENT PowerFactory. 

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3. Agent-Based Modeling Framework for Simulation of Societal Impacts of Infrastructure Service Disruptions during Disasters

   Esmalian, Amir ; Ramaswamy, Maitreyi ; Rasoulkhani, Kambiz ; Mostafavi, Ali ( January 2019 , ASCE Computing in Civil Engineering Workshop)

   The objective of this paper is to model and examine the impacts of different levels of infrastructure service losses caused by disasters on the households’ well-being residing in a community. An agent-based simulation model was developed to capture complex mechanisms underlying households’ tolerance for the service outages, including household characteristics (e.g., sociodemographic, social capital, resources, and previous disaster experience), physical infrastructure attributes, and extreme disruptive events. The rules governing these mechanisms were determined using empirical survey data collected from the residents of Harris County affected by Hurricane Harvey as well as the existing models for power outages and service restoration times. The analysis results highlighted the spatial diffusion of service risks among households living in affected areas in disasters. The proposed simulation model will provide utility agencies with an analytical tool for prioritization of infrastructure service restoration actions to effectively mitigate the societal impacts of service losses. 

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4. Heterogeneity, Household Co-Production, and Risks of Water Services — Water Demand of Private Households with Multiple Water Sources

   https://doi.org/10.1142/S2382624X22500060  

   Zozmann, Heinrich ; Klassert, Christian ; Klauer, Bernd ; Gawel, Erik ( January 2022 , Water Economics and Policy)

   Private households around the world use and combine multiple water sources, including diverse forms of market services and self-supply. The reasons for this have so far not been explained in a coherent framework, nor have the implications for water management and policy been sufficiently analyzed. Here, we examine how heterogeneity of water services, household co-production, and risks of provision influence household demand patterns. We apply an economic household production model that incorporates two water quality levels for different household activities to exemplary situations. We derive a number of explanations why households use and combine water services that expand the current state of research. Relevant findings include: (i) The diverse characteristics of available water services result in different time requirements for water procurement and varying degrees of suitability for household activities. (ii) Differences in the value placed on time can induce households to demand heterogeneous water services because these enable them to find a balance between using time and money to access water. (iii) Certain water services may be demanded because they function as insurance against both uncertain and unreliable supply. Our insights are relevant for water policy, in particular for developing and managing demand-responsive systems, and for the implementation and monitoring of normative goals for access to water. 

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5. A simulation‐based generalized framework to model vulnerability of interdependent critical infrastructure systems under incomplete information

   https://doi.org/10.1111/mice.12999  

   Ganguly, Prasangsha ; Mukherjee, Sayanti ( April 2023 , Computer-Aided Civil and Infrastructure Engineering)

   This paper proposes a novel simulation‐based hybrid approach coupled with time‐dependent Bayesian network analysis to model multi‐infrastructure vulnerability over time under physical, spatial, and informational uncertainties while considering cascading failures within and across infrastructure networks. Unlike existing studies that unrealistically assume that infrastructure managers have full knowledge of all the infrastructure systems, the proposed approach considers a realistic scenario where complete information about the infrastructure network topology or the supply–demand flow characteristics is not available while estimating multi‐infrastructure vulnerability. A novel heuristic algorithm is proposed to construct a dynamic fault tree to abstract the network topology of any infrastructure. In addition, to account for the unavailability of exact supply–demand flow characteristics, the proposed approach constructs the interdependence links across infrastructure network systems using different simulated parameters considering the physical, logical, and geographical dependencies. Finally, using parameters for geographical proximity, infrastructure managers' risk perception, and the relative importance of one infrastructure on another, the multi‐infrastructure vulnerability over time is estimated. Results from the numerical experiment show that for an opportunistic risk perception, the interdependencies attribute to redundancies, and with an increase in redundancy, the vulnerability decreases. On the other hand, from a conservative risk perspective, the interdependencies attribute to deficiencies/liabilities, and the vulnerability increases with an increase in the number of such interdependencies.

    

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