CPIndex: Cyber-Physical Vulnerability Assessment for Power-Grid Infrastructures

2015 ◽  
Vol 6 (2) ◽  
pp. 566-575 ◽  
Author(s):  
Ceeman Vellaithurai ◽  
Anurag Srivastava ◽  
Saman Zonouz ◽  
Robin Berthier
2014 ◽  
Vol 1044-1045 ◽  
pp. 503-506
Author(s):  
Yong Sheng Men ◽  
Long Zhe Jin ◽  
Xi Yuan Xu

Grid infrastructure is vulnerable to damage or breakdown by various of natural disasters and man-made disasters to cause a loss of all or parts of the function of power system. In this paper, through the analysis of various factors affecting the hub substation physical vulnerability of hub substation such as human factors, natural disasters and equipment factors, calculate and classifiy the influence degree of each factor on the physical vulnerability. Put forward a series of suitable vulnerability assessment method for China's national hub substation. What’s more, take a specific hub substation for example to verify the assessment methods that provided a basis for safe operation of power facilities and disasters prevention.


Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 567 ◽  
Author(s):  
Chatura Seneviratne ◽  
Patikiri Arachchige Don Shehan Nilmantha Wijesekara ◽  
Henry Leung

Internet of Things (IoT) can significantly enhance various aspects of today’s electric power grid infrastructures for making reliable, efficient, and safe next-generation Smart Grids (SGs). However, harsh and complex power grid infrastructures and environments reduce the accuracy of the information propagating through IoT platforms. In particularly, information is corrupted due to the measurement errors, quantization errors, and transmission errors. This leads to major system failures and instabilities in power grids. Redundant information measurements and retransmissions are traditionally used to eliminate the errors in noisy communication networks. However, these techniques consume excessive resources such as energy and channel capacity and increase network latency. Therefore, we propose a novel statistical information fusion method not only for structural chain and tree-based sensor networks, but also for unstructured bidirectional graph noisy wireless sensor networks in SG environments. We evaluate the accuracy, energy savings, fusion complexity, and latency of the proposed method by comparing the said parameters with several distributed estimation algorithms using extensive simulations proposing it for several SG applications. Results prove that the overall performance of the proposed method outperforms other fusion techniques for all considered networks. Under Smart Grid communication environments, the proposed method guarantees for best performance in all fusion accuracy, complexity and energy consumption. Analytical upper bounds for the variance of the final aggregated value at the sink node for structured networks are also derived by considering all major errors.


2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Yoonkyung Park ◽  
Ananta Man Singh Pradhan ◽  
Ungtae Kim ◽  
Yun-Tae Kim ◽  
Sangdan Kim

An urban landslide vulnerability assessment methodology is proposed with major focus on considering urban social and economic aspects. The proposed methodology was developed based on the landslide susceptibility maps that Korean Forest Service utilizes to identify landslide source areas. Frist, debris flows are propagated to urban areas from such source areas by Flow-R (flow path assessment of gravitational hazards at a regional scale), and then urban vulnerability is assessed by two categories: physical and socioeconomic aspect. The physical vulnerability is related to buildings that can be impacted by a landslide event. This study considered two popular building structure types, reinforced-concrete frame and nonreinforced-concrete frame, to assess the physical vulnerability. The socioeconomic vulnerability is considered a function of the resistant levels of the vulnerable people, trigger factor of secondary damage, and preparedness level of the local government. An index-based model is developed to evaluate the life and indirect damage under landslide as well as the resilience ability against disasters. To illustrate the validity of the proposed methodology, physical and socioeconomic vulnerability levels are analyzed for Seoul, Korea, using the suggested approach. The general trend found in this study indicates that the higher population density areas under a weaker fiscal condition that are located at the downstream of mountainous areas are more vulnerable than the areas in opposite conditions.


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