Modeling Weather-Related Failures of Overhead Distribution Lines

Zhou, Yujia; Pahwa, Anil; Yang, Shouping

doi:10.1109/tpwrs.2006.881131

Cited by 168 publications

(86 citation statements)

References 10 publications

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“…The quality of data is an important factor to consider in data collection. The reliability database should have a mean of continuous updating and should be flexible enough to output reports in a variety of adequate formats [13].…”

Section: Membership Functions Constructionmentioning

confidence: 99%

Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems

Canizes

Soares

Vale

et al. 2012

Energy

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a b s t r a c tThis paper proposes a new methodology to reduce the probability of occurring states that cause load curtailment, while minimizing the involved costs to achieve that reduction. The methodology is supported by a hybrid method based on Fuzzy Set and Monte Carlo Simulation to catch both randomness and fuzziness of component outage parameters of transmission power system.The novelty of this research work consists in proposing two fundamentals approaches: 1) a global steady approach which deals with building the model of a faulted transmission power system aiming at minimizing the unavailability corresponding to each faulted component in transmission power system. This, results in the minimal global cost investment for the faulted components in a system states sample of the transmission network; 2) a dynamic iterative approach that checks individually the investment's effect on the transmission network.A case study using the Reliability Test System (RTS) 1996 IEEE 24 Buses is presented to illustrate in detail the application of the proposed methodology.

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Section: Membership Functions Constructionmentioning

confidence: 99%

Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems

Canizes

Soares

Vale

et al. 2012

Energy

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“…In (Zhou et al, 2006) BN are used to predict the possibility of faults in the energy distribution, considering some climatic aspects. In this case, a BN is modeled to carry out the fault predictions (in 7 possible states) from the conditions of wind (in 4 states) and the possibility of occurrence of atmospheric discharges (2 states -yes or no).…”

Section: Wwwintechopencommentioning

confidence: 99%

Optimization Strategies for Improving the Interpretability of Bayesian Networks: an Application in Power Systems

Rocha¹,

Cardoso²,

Santana³

et al. 2010

Bayesian Network

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“…First, previous research focuses only on the vulnerability of current electricity networks [14], [17], [20], [21] and does not consider uncertainties and risks from future development and changes. By incorporating a network growth model into the framework, we have simulated the evolution of an electricity network under different infrastructure policies and explored the resilience implications of these policies.…”

Section: Introductionmentioning

confidence: 99%

“…By incorporating a network growth model into the framework, we have simulated the evolution of an electricity network under different infrastructure policies and explored the resilience implications of these policies. Second, assessments usually assume that a network component has a constant failure rate for a given weather condition [16], [21]. Here, a fragility approach, which better reflects the stochastic behavior of real systems, has been employed to investigate the failure probability of a network component.…”

Section: Introductionmentioning

confidence: 99%

Integrated Approach to Assess the Resilience of Future Electricity Infrastructure Networks to Climate Hazards

Wilkinson

Dawson

et al. 2018

IEEE Systems Journal

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Abstract-Electricity systems are undergoing unprecedented change, with growing capacity for low-carbon generation, and an increasingly distributed approach to network control. Furthermore, the severity of climate related threats is projected to increase. To improve our understanding of the risks from these changes, this paper presents a novel modeling approach to assess the resilience of future electricity networks to climate hazards. The approach involves consideration of the: 1) evolution of electricity networks in response to changes in demand, supply, and infrastructure development policies; 2) implication that these policies have on network configuration and resilience; and 3) impacts of potential changes in climate hazard on network resilience. We demonstrate the research on the National Electricity Transmission System of Great Britain and assess the resilience of this system to changes in the intensity of wind storms under alternative energy futures. The analysis shows that infrastructure policies strongly shape the long-term spatial configuration of electricity networks and consequently this has profound impacts on their resilience. Though the system is resilient to wind storms under the current climate, our analysis shows that the system fails to meet electricity demand after an increase of only 5-10% in the intensity and frequency of wind storms, and a 50% increase could lead to the loss of 85% of peak winter demand. The approach is useful for identifying and communicating potential network risks to wider stakeholders and policy makers seeking to design a transition toward a low-carbon, yet resilient, future electricity systems.Index Terms-Complex system modeling, climate change, electricity networks, infrastructure resilience, resilience assessment.

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Modeling Weather-Related Failures of Overhead Distribution Lines

Cited by 168 publications

References 10 publications

Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems

Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems

Optimization Strategies for Improving the Interpretability of Bayesian Networks: an Application in Power Systems

Integrated Approach to Assess the Resilience of Future Electricity Infrastructure Networks to Climate Hazards

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