Distribution System Reliability Assessment Considering Cyber-Physical Integration

Yuan, Hanjie; Li, Gengfeng; Bie, Zhaohong; Arif, Mariyam

doi:10.1016/j.egypro.2019.02.018

Cited by 14 publications

(4 citation statements)

References 10 publications

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“…Yuan et al. [109] proposed that the details of the cyber system cannot be considered in the later assessment of the reliability of the physical system after the method of time series simulation is combined with the cyber‐physical association matrix to obtain the cyber‐physical interface matrix (CPIM) and the auxiliary matrix failure mode consequence matrix (CEM).…”

Section: Modelling and Fragility Analysis Of Mecpssmentioning

confidence: 99%

“…Tang et al [108] proposed the method of the association matrix to build the coupling relationship model of cyber physics and puts forward the fragility assessment indexes of power, communication, and composite system. Yuan et al [109] proposed that the details of the cyber system cannot be considered in the later assessment of the reliability of the physical system after the method of time series simulation is combined with the cyber-physical association matrix to obtain the cyber-physical interface matrix (CPIM) and the auxiliary matrix failure mode consequence matrix (CEM).…”

Section: Ice Disastermentioning

confidence: 99%

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Resilience assessment methodologies and enhancement strategies of multi‐energy cyber‐physical systems of the distribution network

Yang

Liu

et al. 2022

IET Energy Syst Integration

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Natural disasters and cyber intrusions threaten the normal operation of the critical Multi‐Energy Systems (MESs) infrastructures. There is still no universally‐accepted definition of MESs resilience under the integration of cyber and physical, and lack of a widely accepted methodology to quantify and assess the resilience in MESs. Hence, this paper introduces an extensive review of the state‐of‐the‐art research of power systems’ resilience. Then, this work proposes the definition of the Multi‐Energy Cyber‐Physical Systems (MECPSs) resilience and its related characteristics. To improve the resilience of MECPSs, this paper investigates extreme natural disaster models and analyses the vulnerability of the system to find the key constraint factors. Furthermore, this work presents the qualitative assessment curve, quantitative indexes, and assessment framework of the MECPSs resilience. Finally, the key improvement measures for the planning and operation of MECPSs resilience and the focus of future research are presented.

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Section: Modelling and Fragility Analysis Of Mecpssmentioning

confidence: 99%

Section: Ice Disastermentioning

confidence: 99%

Resilience assessment methodologies and enhancement strategies of multi‐energy cyber‐physical systems of the distribution network

Yang

Liu

et al. 2022

IET Energy Syst Integration

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“…With the continuous development and widespread application of communication, automation, and control technology, power systems are gradually evolving into cyber-physical power systems (Yuan et al, 2019). As an essential hub in the power system, the substation also crosses over from a traditional substation to a new generation of intelligent substations with higher intelligence and integration, improving the stability and safety of the substation operation.…”

Section: Introductionmentioning

confidence: 99%

Quantifying and comparing the effects of human and organizational factors in electric maloperation accidents with HFACS–CatBoost and SHAP

Lin

Huang

2022

Hum Ftrs & Erg Mfg Svc

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The proportion of electric maloperation accidents (EMAs) in substations caused by human and organizational factors (HOFs) has gradually increased. Although there has been some research into the factors affecting EMAs in substations, the available results are insufficient to support the interpretation of HOFs in EMAs. This article explores the relationships between the HOFs and EMAs using Human Factors Analysis and Classification System‐gradient boosting with categorical features support (HFACS–CatBoost) and Shapley Additive exPlanation (SHAP) methods. First, the HFACS framework was introduced to identify 135 EMAs in the Southern Power Grid risk causation. CatBoost was used to construct an accident classification model to analyze the important relationship between accidents and HOFs and to compare and analyze with the extreme gradient boosting (XGBoost) and the binary logistic regression (BLR) to verify the superiority of CatBoost. Finally, to solve the problem of inadequate interpretation of the CatBoost black‐box model, the SHAP value plot was applied to express the contribution degree relationship between accidents and HOFs. The results show that the above method can explore and explain the importance and contribution of HOFs in EMAs. And from this, it is concluded that poor psychological state, poor communication and coordination, inadequate supervision, and inadequate training and education are highly correlated with the occurrence of EMAs. The findings will help substation operations and maintenance staff to develop safety measures to address the confusion of HOFs in substations and prevent the occurrence of EMAs.

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“…The paper [12] focuses on developing a comprehensive model to evaluate the impacts of Cyber-Physical Integration on distribution system reliability. This paper proposes a comprehensive model of distribution system reliability assessment considering cyber-physical integration.…”

mentioning

confidence: 99%

The Neural Modules Network with Collective Relearning for the Recognition of Diseases: Fault- Tolerant Structures and Reliability Assessment

Komari

Fedorenko

Kharchenko

et al. 2020

International Journal of Circuits, Systems and Signal Processing

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The article presents the architecture of multi-level information-analytical system (IAS) based on the neural modules network (NMN). This network consists of neural modules which are placed at the three levels (local, region and nation geographically distributed medical centers). Procedures of learning and collectiverelearning of neural modules consider region particularities and are based on analysis, generalization and exchange of experience related to diagnosis of diseases. These procedures provide modification and filtering parameters used as input for the further learning of local and regional neural modules.A few fault-tolerant structures of NMN-based IAS are researched taking into account different options of server and communication redundancy. Reliability block diagrams for redundant IAS structures are developed and formulas for calculation of probability of upstate are analyzed.

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Distribution System Reliability Assessment Considering Cyber-Physical Integration

Cited by 14 publications

References 10 publications

Resilience assessment methodologies and enhancement strategies of multi‐energy cyber‐physical systems of the distribution network

Resilience assessment methodologies and enhancement strategies of multi‐energy cyber‐physical systems of the distribution network

Quantifying and comparing the effects of human and organizational factors in electric maloperation accidents with HFACS–CatBoost and SHAP

The Neural Modules Network with Collective Relearning for the Recognition of Diseases: Fault- Tolerant Structures and Reliability Assessment

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