Imprecise probabilistic framework for power grids risk assessment and sensitivity analysis

Rocchetta, Roberto; Patelli, Edoardo

doi:10.1201/9781315374987-424

Cited by 3 publications

(9 citation statements)

References 9 publications

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“…For the propagation, several methods can be used: double loop MC [23], importance sampling method [24], slicing method [13], multi-level meta-models [16] and, for special classes of problems, analytical methods [25]. In this work, the slicing method is used to propagate P-box uncertainty on the line of previous works [11].…”

Section: Uncertainty Propagation For P-boxesmentioning

confidence: 99%

“…Specifically, each one of its elements d k l quantify the impact of removing a transmission line k on the active flow in the line l, see [33]- [34]- [35] for further details. Thus, provided a pre-outage active flow in the line l (f l ), it is possible to compute directly the post-contingency flow after failure of the line k (f k l ) as follows [11]:…”

Section: Line Outage Distribution Factors (Lodfs)mentioning

confidence: 99%

“…A surrogate model strategy, based on linear approximations of sensitivity indices known as Line Outage Distribution Factors (LODF), is used to reduce the computational cost of each risk evaluations. The surrogate model is embedded within a generalized Uncertainty Quantification (UQ) framework and tested in performing various UQ tasks [11]. Mixed sources of uncertainty are taken into account within the framework and their separate effect quantified in the risk score.…”

Section: Introductionmentioning

confidence: 99%

“…Probability boxes (P-boxes) are a powerful and versatile tool and are used within the framework to model factors affected by mixed sources of uncertainty, see e.g. [12,13,14,15,16,17,11]. Uncertainty propagation and sensitivity analysis quantify the effect of imprecision and inherent variability on the risk index.…”

Section: Introductionmentioning

confidence: 99%

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A post-contingency power flow emulator for generalized probabilistic risks assessment of power grids

Rocchetta

Patelli

2020

Reliability Engineering & System Safety

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In the past decades, risk assessment frameworks have been developed as a viable alternative to Security-Constrained Dispatch for power grids. Risk-based dispatch can increase power grid profitability and help better understanding of prominent hazards, however, relevant sources of uncertainty are often neglected to meet efficiency requirements. In this work, a research effort towards the development of advanced risk assessment frameworks for power grids is presented. A surrogate model strategy is proposed and speeds up the post-contingency consequence evaluation by analytical sensitivity indices (Line-Outage Distribution Factor). The risk surrogate model is embedded within a generalized uncertainty quantification framework to evaluate: (1) The amount of epistemic uncertainty affecting the risk index and attributable to imprecision in the parameters of the model; (2) The effect aleatory uncertainty in environmental-operational variables. The surrogate model is tested on the 24 nodes IEEE Reliability Test System. Computational time and accuracy of the results are compared to a high-fidelity AC power flow risk model. Strengths and weaknesses of the proposed framework highlighted.

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Section: Uncertainty Propagation For P-boxesmentioning

confidence: 99%

Section: Line Outage Distribution Factors (Lodfs)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A post-contingency power flow emulator for generalized probabilistic risks assessment of power grids

Rocchetta

Patelli

2020

Reliability Engineering & System Safety

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“…Nevertheless, generalised probabilistic frameworks provide a valuable perspective on the result and, being non-intrusive, are applicable to 305 any computational model [29]. P-boxes can propagated using different strategies, examples are the double loop Monte Carlo algorithm or the slicing method [37]. Fig.3 presents graphically the two methods.…”

mentioning

confidence: 99%

Assessment of power grid vulnerabilities accounting for stochastic loads and model imprecision

Rocchetta

Patelli

2018

International Journal of Electrical Power & Energy Systems

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© 2017 Elsevier Ltd Vulnerability and robustness are major concerns for future power grids. Malicious attacks and extreme weather conditions have the potential to trigger multiple components outages, cascading failures and large blackouts. Robust contingency identification procedures are necessary to improve power grids resilience and identify critical scenarios. This paper proposes a framework for advanced uncertainty quantification and vulnerability assessment of power grids. The framework allows critical failure scenarios to be identified and overcomes the limitations of current approaches by explicitly considering aleatory and epistemic sources of uncertainty modelled using probability boxes. The different effects of stochastic fluctuation of the power demand, imprecision in power grid parameters and uncertainty in the selection of the vulnerability model have been quantified. Spectral graph metrics for vulnerability are computed using different weights and are compared to power-flow-based cascading indices in ranking N-1 line failures and random N-k lines attacks. A rank correlation test is proposed for further comparison of the vulnerability metrics. The IEEE 24 nodes reliability test power network is selected as a representative case study and a detailed discussion of the results and findings is presented

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A power-flow emulator approach for resilience assessment of repairable power grids subject to weather-induced failures and data deficiency

2018

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© 2017 Elsevier Ltd A generalised uncertainty quantification framework for resilience assessment of weather-coupled, repairable power grids is presented. The framework can be used to efficiently quantify both epistemic and aleatory uncertainty affecting grid-related and weather-related factors. The power grid simulator has been specifically designed to model interactions between severe weather conditions and grid dynamic states and behaviours, such as weather-induced failures or delays in components replacements. A resilience index is computed by adopting a novel algorithm which exploits a vectorised emulator of the power-flow solver to reduce the computational efforts. The resilience stochastic modelling framework is embedded into a non-intrusive generalised stochastic framework, which enables the analyst to quantify the effect of parameters imprecision. A modified version of the IEEE 24 nodes reliability test system has been used as representative case study. The surrogate-based model and the Power-Flow-based model are compared, and the results show similar accuracy but enhanced efficiency of the former. Global sensitivity of the resilience index to increasing imprecision in parameters of the probabilistic model has been analysed. The relevance of specific weather/grid unc ertain factors is highlighted by global sensitivity analysis and the importance of dealing with imprecision in the information clearly emerges

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Imprecise probabilistic framework for power grids risk assessment and sensitivity analysis

Cited by 3 publications

References 9 publications

A post-contingency power flow emulator for generalized probabilistic risks assessment of power grids

A post-contingency power flow emulator for generalized probabilistic risks assessment of power grids

Assessment of power grid vulnerabilities accounting for stochastic loads and model imprecision

A power-flow emulator approach for resilience assessment of repairable power grids subject to weather-induced failures and data deficiency

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