Evaluation of hurricane impact on composite power system reliability considering common-cause failures

Liu, Yong; Singh, Chanan

doi:10.1007/s13198-010-0024-7

Cited by 26 publications

(18 citation statements)

References 19 publications

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“…Several studies have been developed in order to quantitatively assess power systems resilience to natural hazards and extreme weather [13][14][15][16][17][18][19][20][21][22][23][24].…”

Section: Quantitative Resilience Metricsmentioning

confidence: 99%

“…10 shows an example of applying the resilience enhancement strategies considered in the previous section, i.e., making the transmission lines 20% more robust and responsive respectively, based on the RAW index of each transmission corridor. These strategies are subsequently applied to groups of five lines depending on their criticality, i.e., first applied to the first five more critical lines (with IDs 45,34,29,41 and 38), then to the first ten more critical lines (with IDs 45,34,29,41,38,19,42,44,20 and 18) and so on until all fifty circuits of the test network become more robust and responsive respectively. It can be clearly seen that making the lines more robust has a higher effect than improving the responsiveness, i.e., reducing their restoration time.…”

Section: E Systematic Approach For Resilience Enhancementmentioning

confidence: 99%

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Power Systems Resilience Assessment: Hardening and Smart Operational Enhancement Strategies

et al. 2017

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Abstract-Power systems have typically been designed to be reliable to expected, low-impact high-frequency outages. In contrast, extreme events, driven for instance by extreme weather and natural disasters, happen with low-probability, but can have a high impact. The need for power systems, possibly the most critical infrastructures in the world, to become resilient to such events is becoming compelling. However, there is still little clarity as to this relatively new concept. On these premises, this paper provides an introduction to the fundamental concepts of power systems resilience and to the use of hardening and smart operational strategies to improve it. More specifically, first the resilience trapezoid is introduced as visual tool to reflect the behavior of a power system during a catastrophic event. Building on this, the key resilience features that a power system should boast are then defined, along with a discussion on different possible hardening and smart, operational resilience enhancement strategies. Further, the so-called ΦΛΕΠ resilience assessment framework is presented, which includes a set of resilience metrics capable of modelling and quantifying the resilience performance of a power system subject to catastrophic events. A case study application with a 29-bus test version of the Great Britain transmission network is carried out to investigate the impacts of extreme windstorms. The effects of different hardening and smart resilience enhancement strategies are also explored, thus demonstrating the practicality of the different concepts presented. However, ensuring an uninterrupted electricity supply is challenging, as power systems are exposed to several threats. These threats can be mainly categorized in typical power system outages and extreme events, driven for instance by natural disasters/extreme weather. There are distinct differences between these two categories, as shown in Table I [4]. Hence, electrical power systems have been designed in a way that they possess high levels of reliability to the more typical threats. Latest events are now creating compelling cases for power systems to also boast high levels of resilience to natural disasters and extreme weather, to reduce the frequency and severity of power disruptions. Power systems reliability is a well-known and established concept, and several reliability-oriented studies have been developed by power system engineers and scholars. In contrast, there is much less clarity as to the concept of resilience. "Resilience" originates from the Latin word "resilio" and, having been first introduced by C.S. Holling in 1973 for ecological systems [5], is a relatively new and emerging concept in the area of power systems. Within this context, power systems resilience can be referred to as the ability of a power system to recover quickly following a disaster or, more generally, to the ability of anticipating extraordinary and high-impact, low-probability events, rapidly recovering from these disruptive events, and absorbing lessons for adapting ...

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“…Several studies have been developed in order to quantitatively assess power systems resilience to natural hazards and extreme weather [13][14][15][16][17][18][19][20][21][22][23][24].…”

Section: Quantitative Resilience Metricsmentioning

confidence: 99%

Section: E Systematic Approach For Resilience Enhancementmentioning

confidence: 99%

Power Systems Resilience Assessment: Hardening and Smart Operational Enhancement Strategies

et al. 2017

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“…Similar learning-based methods are proposed in [20][21][22] for approximate CPS reliability modelling and hurricane impact modelling by BN. Learning is a general time-consuming method to determine BN model of any system which does not consider special features of CPS in reliability assessment.…”

Section: Literature Reviewmentioning

confidence: 99%

“…(4) All input probabilities and computed indices are steady-state values (regarding BN capabilities, the proposed method is also applicable to time specific case using the repetitive temporal model [22]). (5) Although the BN model has no limit to model the components failures as discrete or continuous variables or mixed of them, here failure probabilities are considered as discrete variables.…”

Section: Bn For Cps Reliability Evaluationmentioning

confidence: 99%

Application of Bayesian networks in composite power system reliability assessment and reliability‐based analysis

Eliassi

Dashtaki

Seifi

et al. 2015

IET Generation, Transmission & Distribution

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Bayesian network (BN) is a strong framework for handling probabilistic events which have received limited attention in power system reliability assessment. By applying BN for bulk power system reliability assessment, additional capabilities are provided at modelling and analysis levels in comparison with conventional methods. This study proposes a methodology to apply BNs to composite power system (CPS) reliability modelling, reliability assessment and reliability-based analyses. A minimal cutset (MC)-based method is proposed to extract the BN structure. Moreover, BN parameters are defined based on logical relationships between components, MCs and system failure. In addition, some issues of BN application to large systems are investigated. A variety of reliability-based analyses, useful in different power system studies are introduced and discussed in details which are provided by applying BNs to CPS reliability. The computational efficiency of the presented method is demonstrated by comparing it with state enumeration and Monte Carlo simulation methods. The proposed methodology is implemented on Roy Billinton Test System to extract its BN model based on which analysis issues are considered. Finally, the proposed methodology is applied to the simple, but representative, system the IEEE-reliability test system to show its feasibility in larger systems.

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“…For example, the noisy OR-gate model, regression model and fuzzy model are proposed in many literatures [22][23][24][25]. In these methods, the average failure rate model is still used after data splitting and aggregation.…”

Section: Introductionmentioning

confidence: 99%

Failure probability estimation of overhead transmission lines considering the spatial and temporal variation in severe weather

Yang

Zhou

Zhu³

et al. 2018

J. Mod. Power Syst. Clean Energy

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Estimation for weather-related failure probability of overhead transmission lines is essential in the reliability assessment of a power system. This paper analyzes the outage and weather data of 110 kV overhead transmission lines in the Guangxi Zhuang Autonomous Region of China during 2011-2014. The result reveals obvious uneven distributions of outage events for time and space due to the spatial and temporal variation of severe weather. Based on the results, an estimation method is proposed in this paper. Split and aggregation is used to smooth the outage and weather data. The poisson model is adopted in our method to investigate the statistic characteristics of transmission line outage events. Regression analysis is applied to obtain the correlation between the weather intensity and history failure rate. Furthermore the method proposed is validated against the empirical outage data.

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Evaluation of hurricane impact on composite power system reliability considering common-cause failures

Cited by 26 publications

References 19 publications

Power Systems Resilience Assessment: Hardening and Smart Operational Enhancement Strategies

Power Systems Resilience Assessment: Hardening and Smart Operational Enhancement Strategies

Application of Bayesian networks in composite power system reliability assessment and reliability‐based analysis

Failure probability estimation of overhead transmission lines considering the spatial and temporal variation in severe weather

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