Dynamic Probabilistic Risk Assessment of Cascading Outages · 2015. 11. 4. · Introduction •Main probabilistic risk assessment tools of cascading outages: “static” or Quasi-Steady-State

Dynamic Probabilistic Risk Assessment of Cascading

Outages

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P. Henneaux J. Song E. Cotilla-Sanchez

Tractebel Engineering

Université libre de Bruxelles

Oregon State University

Oregon State University

Acknowledgements

• Paul Hines and Goodarz Ghanavati (University of Vermont)

• Pierre-Etienne Labeau and Jean-Claude Maun (Université libre de Bruxelles)

• Daniel Kirschen (University of Washington)

• Karim Karoui (Tractebel Engineering)

• …

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Introduction

• Main probabilistic risk assessment tools of cascading outages: “static” or Quasi-Steady-State (QSS) (power flow equations)

– OPA, Manchester model, TRELSS (TransCare), PCM (previous release)…

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Steady-state (power flow/OPF)

Initiating event (initial outage/set

of outages)

Additional outages

(overload,under/overvoltage…)

?

Yes

End of cascade

No

Introduction

• Several cascading phenomena are intrinsically dynamic (angular instability, frequency instability…)

– Important to consider them in a probabilistic risk assessment of cascading outages?

– How to consider them?

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Introduction

• Goals of this presentation

– Claim that dynamic phenomena should be included in a probabilistic risk assessment of cascading outages

– Present methodologies of dynamic modeling of cascading outages

– Discuss the importance of stochastic behavior of protection systems

– Discuss possible tools: commercial software versus research-grade software

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Agenda

• Introduction

• The need for dynamic PRA

• Methodologies

• Misoperation of protection systems

• Commercial and research grade softwares

• Conclusions

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Agenda

• Introduction


• Methodologies



• Conclusions

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The need for dynamic PRA

• Modeling environments required for main cascading mechanisms

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Mechanism Modeling environment required

Branch outages by OC and DIST relays Static/Dynamic

Branch outages by thermal failures Static/Dynamic

Unexpected trips due to hidden failures

Static/Dynamic

Transient instability Dynamic

Frequency instability Dynamic

Small-disturbance angular instability Dynamic


• Importance of dynamic phenomena in past blackouts: Italy, 2003

– Initially, succession of overloads…

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Static: OK


• Importance of dynamic phenomena in past blackouts?

– But, after isolation of Italy, frequency instability

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Static: OK


• Comparison of static and dynamic simulations

– Italian Transmission System: events after the loss of a large thermal power plant in Southern Italy

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E. Ciapessoni, D. Cirio, and A. Pitto, “Cascadings in large power systems: benchmarking static vs. time

domain simulation,” in Proceedings of the 2014 IEEE PES GM.

Static: OK

Static: OK


• Comparison of static and dynamic simulations

– Polish case: impact of N-2 contingencies

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J. Song, E. Cotilla-Sanchez, G. Ghanavati and P. Hines, “Dynamic Modeling of Cascading

Failure in Power Systems,” IEEE Transactions on Power Systems, Accepted for publication

(IEEE Xplore - Early access, DOI: 10.1109/TPWRS.2015.2439237).

Underestimation of the

probability of large disturbances!

Agenda

• Introduction


• Methodologies



• Conclusions

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Methodologies

• Deterministic electrical dynamic simulations

• Deterministic electrical & thermal dynamic simulations

• Probabilistic electrical dynamic simulations

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Methodologies




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Methodologies


– Only outages due to electrical protection systems are considered

– Protection systems are considered as perfectly reliable

– E.g. Pegase Project (http://www.fp7-pegase.com/), D6.3: deterministic dynamic simulations of cascading outages to train system operators (2012)

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http://www.fp7-pegase.com/



Methodologies




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Methodologies


– Importance of “thermal failures” in past cascading outages (especially in the beginning)

– Need to include this cascading mechanism in a simulation

– OSU & UVM developed an ad-hoc simulator, COSMIC (http://github.com/ecotillasanchez/cosmic)

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http://github.com/ecotillasanchez/cosmic


Methodologies




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Methodologies


– Protection systems do not always act as expected (e.g. hidden failures)

– Need to include stochastic behaviors of protection systems in the dynamic simulation → probabilistic dynamic simulation

– Probabilistic dynamic simulations initially developed at Iowa State University for operational defense of cascading events (see Q. Chen, “The probability, identification, and prevention of rare events in power systems,” PhD thesis, 2003)

– Probabilistic dynamic simulator under development by Tractebel Engineering, based on the deterministic simulator Eurostag (http://www.eurostag.be/)

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http://www.eurostag.be/

Methodologies

• Example of a deterministic electrical & thermal dynamic simulation (COSMIC) – Polish test system

– Events after a N-2 contingency

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Methodologies

• Example of a deterministic electrical & thermal dynamic simulation (COSMIC) – Polish test system

– Risks induced by N-2 contingencies for different load models

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Methodologies

• Example of a probabilistic electrical dynamic simulations (Eurostag) – Reliability Test System

– Consideration of protection system misoperations (measurement errors, circuit breaker failures, timer failures…)

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P. Henneaux, P.-E. Labeau, J.-C. Maun and L. Haarla, “A two-level Probabilistic Risk Assessment

of cascading outages,” IEEE Transactions on Power Systems, Accepted for publication.

Agenda

• Introduction


• Methodologies


• Commercial/research grade software

• Conclusions

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Misoperation of protection systems

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• Protection systems not perfectly reliable

– Missing trips/unwanted trips

– Importance to consider these misoperations in dynamic simulation of cascading outages?

– For a specific initiating event in precise pre-contingency steady state, obviously important

• If all protections act as expected, one unique outcome

• If possible failures, different outcomes

– But impact on the global risk?


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• Impact of misoperations on a small system

– Adaptation of Kundur’s two-area test system, Monte Carlo simulation (sampling of thresholds & failures)


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• Impact of misoperations on a large system

– Polish test case (2383-bus test system), idem

Agenda

• Introduction


• Methodologies



• Conclusions

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Commercial/research-grade software

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Commercial software Research-grade tool

Pros • Available models for a large number of modern power systems components

• Optimized numerical efficiency

• In-depth access to the source code, and allows precise tuning of modeling/control assumptions

• Easy to integrate in a HPC cluster • Cost

Cons • Black box, difficult to adapt • Difficult to integrate in a HPC

cluster • Cost

• Models not always available for each power system component (e.g. HVDC, wind farms…)

• Weaker numerical efficiency

Example Eurostag (http://www.eurostag.be/)

COSMIC (http://github.com/ecotillasanchez/cosmic)

http://www.eurostag.be/


Agenda

• Introduction


• Methodologies



• Conclusions

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Conclusions

• Importance of dynamic mechanisms in cascading outages

– Especially in the latter stage

• Different degrees of complexity in existing models

– Methodologies still under development (HRs needed!)

• Importance of misoperation of protection systems?

– Not yet clear

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Dynamic Probabilistic Risk Assessment of Cascading Outages · 2015. 11. 4. · Introduction •Main probabilistic risk assessment tools of cascading outages: “static” or Quasi-Steady-State