Availability-based engineering resilience metric and its corresponding evaluation methodology

Cai, Baoping; Xie, Min; Liu, Yonghong; Liu, Yiliu; Qing, Feng

doi:10.1016/j.ress.2017.12.021

Cited by 212 publications

(85 citation statements)

References 45 publications

(47 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A dynamic Bayesian network-based method has been proposed in [68] to evaluate the resilience of power grids. The structural and maintenance resources have been considered as the main elements of resilience in [68] and failure probabilities are evaluated for both with and without external shocks. Power system states (success and failure) are represented by the sates of nodes.…”

Section: E Bayesian Network-based Methodsmentioning

confidence: 99%

“…Reliability-based metrics have been proposed in [65]- [68] to quantify the resilience of power systems. In [65], a time series analysis-based system resilience approach has been developed to provide a relationship between loss of load frequency (LOLF), energy not supplied (ENS), loss of load expectation (LOLE), capacity margin, and the frequency and intensity of storms.…”

Section: Reliability-based Metricsmentioning

confidence: 99%

“…In [67], four metrics have been proposed to measure the impacts of extreme events on MGs: (i) a metric (metric-K) that is used to measure the expected number of lines outages due to destructive events; (ii) LOLP is used to measure the loss of load due to extreme events; (iii) expected demand not supplied (EDNS) is used to measure the expected demand not supplied due to extreme events; and (iv) a metric (metric-G) that is used to measure the difficulty level of grid recovery. In addition, a resilience metric based on the availability of system components has been proposed in [68]. This metric captures both time and performance-related properties of the system before and after disasters using steady-state availability and event time.…”

Section: Reliability-based Metricsmentioning

confidence: 99%

“…This metric captures both time and performance-related properties of the system before and after disasters using steady-state availability and event time. The proposed metrics in [68] are evaluated by multiplying the ratio of availability and the natural logarithm of recovery time before and after external shock.…”

Section: Reliability-based Metricsmentioning

confidence: 99%

See 3 more Smart Citations

Power System Resilience: Current Practices, Challenges, and Future Directions

et al. 2020

View full text Add to dashboard Cite

The frequency of extreme events (e.g., hurricanes, earthquakes, and floods) and man-made attacks (cyber and physical attacks) has increased dramatically in recent years. These events have severely impacted power systems ranging from long outage times to major equipment (e.g., substations, transmission lines, and power plants) destructions. This calls for developing control and operation methods and planning strategies to improve grid resilience against such events. The first step toward this goal is to develop resilience metrics and evaluation methods to compare planning and operation alternatives and to provide techno-economic justifications for resilience enhancement. Although several power system resilience definitions, metrics, and evaluation methods have been proposed in the literature, they have not been universally accepted or standardized. This paper provides a comprehensive and critical review of current practices of power system resilience metrics and evaluation methods and discusses future directions and recommendations to contribute to the development of universally accepted and standardized definitions, metrics, evaluation methods, and enhancement strategies. This paper thoroughly examines the consensus on the power system resilience concept provided by different organizations and scholars and existing and currently practiced resilience enhancement methods. Research gaps, associated challenges, and potential solutions to existing limitations are also provided. INDEX TERMS Critical review, extreme events, power system resilience, resilience definitions, metrics, and enhancement strategies. MOHAMMED BENIDRIS (Member, IEEE) received the B.Sc. and M.Sc. degrees in electrical engineering from the

show abstract

Section: E Bayesian Network-based Methodsmentioning

confidence: 99%

Section: Reliability-based Metricsmentioning

confidence: 99%

Section: Reliability-based Metricsmentioning

confidence: 99%

Section: Reliability-based Metricsmentioning

confidence: 99%

See 2 more Smart Citations

Power System Resilience: Current Practices, Challenges, and Future Directions

et al. 2020

View full text Add to dashboard Cite

show abstract

“…In the field of network security, Bayesian network was used to assess the online public opinions and to predict the interactive relationship among different people [14]; In the field of emergency management, Bayesian network model was constructed to predict emergencies and to assess the main states and loss consequences [15]; In the field of fault diagnosis, Bayesian network (BN) is increasingly utilized in fault diagnosis to effectively deal with various uncertainty problems [16]. Bayesian network model was integrated with event tree and other models to investigate emergency response experiences contained in massive emergency cases [17]; A dynamic-Bayesian-network-based evaluation methodology was used to predict the resilience value of an engineering system [18]. Bayesian network was also used to analyze the usual causes of failures and the dependencies among the variables in dust explosion scenarios [19]; Similarly, it turned out to be effective that the scenario analysis was combined with Bayesian network to evaluate the occurrence probability of mine water inrush accident and the hazard evolution, performing the disaster response [20].…”

Section: Related Workmentioning

confidence: 99%

Risk Analysis of Urban Dirty Bomb Attacking Based on Bayesian Network

Tang

et al. 2019

Sustainability

View full text Add to dashboard Cite

Urban dirty bomb attacking is a type of unconventional terrorism threatening the urban security all through the world. In this paper, a Bayesian network of urban dirty bomb attacking is established to analyze the risk of urban dirty bomb attacking. The impacts of factors such as occurrence time, location, wind fields, the size of dirty bomb, emergency response and defense approaches on casualty from both direct blast and radiation-caused cancers are examined. Results show that sensitivity of casualty from cancers to wind fields are less significant; the impact of emergency response on the direct casualty from blast is not large; the size of the dirty bomb results in more casualties from cancers than that from bomb explosions; Whether an attack is detected by the police is not that related to normal or special time, but significantly depends on the attack location; Furthermore, casualty from cancers significantly depends on the location, while casualty from blast is not considerably influenced by the attacking location; patrol and surveillance are less important than security check in terms of controlling the risk of urban dirt bomb, and security check is the most effective approach to decreasing the risk of urban dirty bomb.

show abstract

A novel planning‐attack‐reconfiguration method for enhancing resilience of distribution systems considering the whole process of resiliency

Wang

et al. 2019

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary To enhance the resilience of distribution systems and fight against extreme disasters, a novel planning‐attack‐reconfiguration optimization method is proposed in this paper. Firstly, according to the processes of prevention, defence, and restoration for a resilient distribution system through disruption, the novel resilience evaluation indicators are presented, which include the node degree of distributed generation (DG) bus, survival rate, and recovery ability. Secondly, a novel planning‐attack‐reconfiguration optimization model is developed to improve the resilience of distribution systems. In DG planning stage, the multi‐objective planning model is formulated, which includes the minimization of the total cost of investment and operation, and the maximization of the node degree of DG buses for critical loads. In the attack stage, a clear worst case of N‐k contingencies on the basis of generalized nodes is presented to reduce the computational complexity. Then, the post‐disaster network reconfiguration model is formulated to maximize the restoration rate of critical loads (RRCL). Finally, the proposed method is illustrated by the case study on PG&E 69‐bus distribution system. The simulation results indicate that all the RRCL can reach about 90% in the four multipoint fault scenarios. Meanwhile, other evaluation indicators are greatly improved. It is shown that the resilience of distribution systems can be dramatically enhanced by the proposed method.

show abstract

Availability-based engineering resilience metric and its corresponding evaluation methodology

Cited by 212 publications

References 45 publications

Power System Resilience: Current Practices, Challenges, and Future Directions

Power System Resilience: Current Practices, Challenges, and Future Directions

Risk Analysis of Urban Dirty Bomb Attacking Based on Bayesian Network

A novel planning‐attack‐reconfiguration method for enhancing resilience of distribution systems considering the whole process of resiliency

Contact Info

Product

Resources

About