A “Random Chemistry” Algorithm for Identifying Collections of Multiple Contingencies That Initiate Cascading Failure

Eppstein, Margaret J.; Hines, Paul

doi:10.1109/tpwrs.2012.2183624

Cited by 262 publications

(174 citation statements)

References 23 publications

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“…The simulation is repeated until there are no overloaded lines or transformers in the process of cascading outages. The sequence of the cascading model of the transmission line is as follows [17,18]. First, the probability of outage is calculated, according to the following equation.…”

Section: Screening Methodology For Estimating the Eensmentioning

confidence: 99%

Estimation for Expected Energy Not Served of Power Systems Using the Screening Methodology of Cascading Outages in South Korea

Goo

Hur

2017

Energies

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Abstract:The uncertainty of complex power systems increases the possibility of large blackouts due to the expectations of physical events, such as equipment failures, protection failures, control actions failure, operator error, and cyber-attacks. Cascading outage is a sequence of dependent failures of individual components that successively weaken the power system. A procedure to identify and evaluate the initiating events and perform sequential cascading analysis is needed. In this paper, we propose a new screening methodology based on sequential contingency simulation of cascading outages, including probabilistic analysis and visualization model. Performance of a detail cascading analysis using practical power systems is suggested and discussed. The proposed screening methodology will play a key role in identifying the uncontrolled successive loss of system elements.

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Section: Screening Methodology For Estimating the Eensmentioning

confidence: 99%

Estimation for Expected Energy Not Served of Power Systems Using the Screening Methodology of Cascading Outages in South Korea

Goo

Hur

2017

Energies

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“…In the second step of our solution approach, and particularly the computation of the residual risk for the evaluation of (8), we have implemented the cascading failure simulator presented in [14], which is a modified version of the model originally introduced in [15]. Referring the interested reader to [14], [15] for a detailed presentation of this simulation model, we should briefly introduce that this DC power flow based algorithm starts from any triggering event and involves the sequential simulation of relay-based trippings of overloaded branches, generator trippings and load shedding events, while taking into account the accumulated overloading of any branch over time to define the temporal characteristics of the cascade evolution process.…”

Section: B Mathematical Model Used In the Implementationmentioning

confidence: 99%

“…Referring the interested reader to [14], [15] for a detailed presentation of this simulation model, we should briefly introduce that this DC power flow based algorithm starts from any triggering event and involves the sequential simulation of relay-based trippings of overloaded branches, generator trippings and load shedding events, while taking into account the accumulated overloading of any branch over time to define the temporal characteristics of the cascade evolution process.…”

Section: B Mathematical Model Used In the Implementationmentioning

confidence: 99%

Probabilistic Reliability Management Approach and Criteria for power system real-time operation

Karangelos

Wehenkel

2016

2016 Power Systems Computation Conference (PSCC)

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Abstract-This paper develops a probabilistic approach for power system reliability management in real-time operation where risk is a product of i) the potential occurrence of contingencies, ii) the possible failure of corrective (i.e., post-contingency) control and, iii) the socio-economic impact of service interruptions to end-users. Stressing the spatiotemporal variability of these factors, we argue for reliability criteria assuring a high enough probability of avoiding service interruptions of severe socio-economic impact by dynamically identifying events of nonnegligible implied risk. We formalise the corresponding decision making problem as a chance-constrained two-stage stochastic programming problem, and study its main features on the single area IEEE RTS-96 system. We also discuss how to leverage this proposal for the construction of a globally coherent reliability management framework for long-term system development, midterm asset management, and short-term operation planning.

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“…A unique aspect of the Random Chemistry algorithm (see Appendix I and [25]) is that it is designed to find "minimal" blackout-causing contingencies. A minimal blackout-causing contingency is a set of outages that result in a large blackout (in this paper we define large as ≥ 5%), but would not result in a large blackout if any one of the outages in the multiple-contingency had not occurred.…”

Section: A Risk From Minimal Contingenciesmentioning

confidence: 99%

“…In our prior work [25], we adapted a search algorithm, known as Random Chemistry (RC), to the problem of finding large collections of n − k contingencies that lead to cascading failure. However, this initial work did not explain how the approach could be used for risk estimation.…”

Section: Introductionmentioning

confidence: 99%

Estimating Cascading Failure Risk With Random Chemistry

Rezaei

Hines

Eppstein

2015

IEEE Trans. Power Syst.

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Abstract-The potential for cascading failure in power systems adds substantially to overall reliability risk. Monte Carlo sampling can be used with a power system model to estimate this impact, but doing so is computationally expensive. This paper presents a new approach to estimating the risk of large cascading blackouts triggered by multiple contingencies. The method uses a search algorithm (Random Chemistry) to identify blackoutcausing contingencies, and then combines the results with outage probabilities to estimate overall risk. Comparing this approach with Monte Carlo sampling for two test cases (the IEEE RTS-96 and a 2383 bus model of the Polish system) illustrates that the new approach is at least two orders of magnitude faster than Monte Carlo, without introducing measurable bias. Moreover, the approach enables one to compute the sensitivity of overall blackout risk to individual component-failure probabilities in the initiating contingency, allowing one to quickly identify low-cost strategies for reducing risk. By computing the sensitivity of risk to individual initial outage probabilities for the Polish system, we found that reducing three line-outage probabilities by 50% would reduce cascading failure risk by 33%. Finally, we used the method to estimate changes in risk as a function of load. Surprisingly, this calculation illustrates that risk can sometimes decrease as load increases.

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A “Random Chemistry” Algorithm for Identifying Collections of Multiple Contingencies That Initiate Cascading Failure

Cited by 262 publications

References 23 publications

Estimation for Expected Energy Not Served of Power Systems Using the Screening Methodology of Cascading Outages in South Korea

Estimation for Expected Energy Not Served of Power Systems Using the Screening Methodology of Cascading Outages in South Korea

Probabilistic Reliability Management Approach and Criteria for power system real-time operation

Estimating Cascading Failure Risk With Random Chemistry

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