International journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN:2313-626X

Frequency: 12
line decor
  
line decor

 Volume 6, Issue 11 (November 2019), Pages: 68-74

----------------------------------------------

 Original Research Paper

 Title: Evaluation of power system reliability levels for (n-1) outage contingency

 Author(s): Badr M. Alshammari *

 Affiliation(s):

 Electrical Department, College of Engineering, University of Ha’il, Saudi Arabia

  Full Text - PDF          XML

 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0001-6819-3695

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2019.11.009

 Abstract:

Throughout the world, power utilities have been struggling relentlessly with the delicate balance between cost and security/reliability. The experience gained by the power utilities at the Kingdom of Saudi Arabia has been similar to that of many public and private utilities around the world. In conjunction with energy conservation, power system security and reliability evaluation has grown to constitute a subject of prime interest. This paper presents, illustrative practical applications to evaluate power System reliability based on the (n-1) contingency. Therefore, the methodology is demonstrated in this paper, is based on combined between the evaluation of the reliability indices and contingency analysis. The methodology has been successfully applied to portions of a practical power system representing the Saudi electricity grid, where composite system performance reliability indices have been evaluated. The model System which is used contains hundreds of buses and tens of complex stations and analyzed using advanced and numerically effective large-scale computer scheme. 

 © 2019 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Power system reliability, Contingency, Large-scale system, Power system

 Article History: Received 9 February 2019, Received in revised form 2 September 2019, Accepted 5 September 2019

 Acknowledgement:

This research work was supported by University of Ha’il.

 Compliance with ethical standards

 Conflict of interest:  The authors declare that they have no conflict of interest.

 Citation:

 Alshammari BM (2019). Evaluation of power system reliability levels for (n-1) outage contingency. International Journal of Advanced and Applied Sciences, 6(11): 68-74

 Permanent Link to this page

 Figures

 Fig. 1 Fig. 2

 Tables

 Table 1 Table 2 Table 3 Table 4 

----------------------------------------------

 References (28) 

  1. Billinton R (1970). Power system reliability evaluation. Taylor and Francis, Abingdon, UK.   [Google Scholar]
  2. Chen Q, Jiang C, Qiu W, and McCalley JD (2006). Probability models for estimating the probabilities of cascading outages in high-voltage transmission network. IEEE Transactions on Power Systems, 21(3): 1423-1431. https://doi.org/10.1109/TPWRS.2006.879249   [Google Scholar]
  3. Chen Q, Lin Y, and McCalley JD (2007). The risk of high-order transmission contingencies. In the 2007 IEEE Power Engineering Society General Meeting, IEEE, Tampa, USA: 1-7. https://doi.org/10.1109/PES.2007.385902   [Google Scholar]
  4. Choi J, Mount TD, Thomas RJ, and Billinton R (2006). Probabilistic reliability criterion for planning transmission system expansions. IEE Proceedings-Generation, Transmission and Distribution, 153(6): 719-727. https://doi.org/10.1049/ip-gtd:20050205   [Google Scholar]
  5. Ciapessoni E, Cirio D, Massucco S, and Pitto A (2011). A risk-based methodology for operational risk assessment and control of power systems. In the 17th Power Systems Computation Conference, Stockholm, Sweden: 1-7.   [Google Scholar]
  6. Daram SB, Venkataramu PS, and Nagaraj MS (2016). Performance index based contingency ranking under line outage condition incorporating IPFC. In the International Conference on Electrical, Electronics, and Optimization Techniques, IEEE, Chennai, India: 2589-2593. https://doi.org/10.1109/ICEEOT.2016.7755161   [Google Scholar]
  7. de Jong M, Papaefthymiou G, and Palensky P (2018). A framework for incorporation of infeed uncertainty in power system risk-based security assessment. IEEE Transactions on Power Systems, 33(1): 613-621. https://doi.org/10.1109/TPWRS.2017.2687983   [Google Scholar]
  8. Dobson I (2012). Estimating the propagation and extent of cascading line outages from utility data with a branching process. IEEE Transactions on Power Systems, 27(4): 2146-2155. https://doi.org/10.1109/TPWRS.2012.2190112   [Google Scholar]
  9. El-Kady MA, El-Sobki MS, and Sinha NK (1985). Loss of load probability evaluation based on real-time emergency dispatch. Canadian Electrical Engineering Journal, 10(2): 57-60. https://doi.org/10.1109/CEEJ.1985.6592019   [Google Scholar]
  10. El-Kady MA, El-Sobki MS, and Sinha NK (1986). Reliability evaluation for optimally operated, large, electric power systems. IEEE Transactions on Reliability, 35(1): 41-47. https://doi.org/10.1109/TR.1986.4335340   [Google Scholar]
  11. Endrenyi J (1978). Reliability modeling in electric power systems. Wiley, New York, USA.   [Google Scholar]
  12. Gomez-Exposito A, Conejo AJ, and Canizares C (2018). Electric energy systems: Analysis and operation. CRC Press, Boca Raton, USA. https://doi.org/10.1201/9781420007275   [Google Scholar] PMid:29326674 PMCid:PMC5741648
  13. Grijalva S and Roy A (2013). Automated handling of arbitrary switching device topologies in planning contingency analysis: Towards temporal interoperability in network security assessment. IEEE Transactions on Power Systems, 28(2): 1523-1530. https://doi.org/10.1109/TPWRS.2012.2215057   [Google Scholar]
  14. Hardiman RC, Kumbale M, and Makarov YV (2004). An advanced tool for analyzing multiple cascading failures. In the International Conference on Probabilistic Methods Applied to Power Systems, IEEE, Ames, USA: 629-634.   [Google Scholar]
  15. Henneaux P, Faghihi F, Labeau PE, and Maun JC (2013). Towards a 3-level blackout probabilistic risk assessment: Achievements and challenges. In the IEEE Power and Energy Society General Meeting, IEEE, Vancouver, Canada: 1-5. https://doi.org/10.1109/PESMG.2013.6672067   [Google Scholar]
  16. ICR (1966). Proposed definitions of terms for reporting and analyzing outages of generating equipment. IEEE Committee Report, IEEE Transactions on Power Apparatus and Systems, PAS-85 (4): 390-393. https://doi.org/10.1109/TPAS.1966.291576   [Google Scholar]
  17. ICR (1968). Proposed definitions of terms of reporting and analyzing outages of electrical transmission and distribution facilities and interruptions. IEEE Committee Report, IEEE Transactions on Power Apparatus and Systems, PAS-87: 1318-1323. https://doi.org/10.1109/TPAS.1968.292224   [Google Scholar]
  18. Koenig M, Duggan P, Wong J, Vaiman MY, Vaiman MM, and Povolotskiy M (2010). Prevention of cascading outages in Con Edison's network. In the IEEE PES T&D 2010, IEEE, New Orleans, USA: 1-7. https://doi.org/10.1109/TDC.2010.5484278   [Google Scholar]
  19. Lee ST (2008). Estimating the probability of cascading outages in a power grid. In the 16th Power Systems Computation Conference, Glasgow, Scotland: 14-18.   [Google Scholar]
  20. Li X, Balasubramanian P, Sahraei-Ardakani M, Abdi-Khorsand M, Hedman KW, and Podmore R (2017). Real-time contingency analysis with corrective transmission switching. IEEE Transactions on Power Systems, 32(4): 2604-2617. https://doi.org/10.1109/TPWRS.2016.2616903   [Google Scholar]
  21. Makarov YV, Samaan N, Diao R, Kumbale M, Chen Y, Singh R, and Morgan MP (2011). Assessment of critical events corridors through multivariate cascading outages analysis. In the IEEE Power and Energy Society General Meeting, IEEE, Detroit, USA: 1-8. https://doi.org/10.1109/PES.2011.6039900   [Google Scholar]
  22. Miller SS (2008). Extending traditional planning methods to evaluate the potential for cascading failures in electric power grids. In the IEEE Power and Energy Society General Meeting-Conversion and Delivery of Electrical Energy in the 21st Century, IEEE, Pittsburgh, USA: 1-7. https://doi.org/10.1109/PES.2008.4596768   [Google Scholar]
  23. Pandzic H, Dvorkin Y, Qiu T, Wang Y, and Kirschen DS (2016). Toward cost-efficient and reliable unit commitment under uncertainty. IEEE Transactions on Power Systems, 31(2): 970-982. https://doi.org/10.1109/TPWRS.2015.2434848   [Google Scholar]
  24. Pérez-Londoño SM, Olivar-Tost G, and Mora-Florez JJ (2017). Online determination of voltage stability weak areas for situational awareness improvement. Electric Power Systems Research, 145: 112-121. https://doi.org/10.1016/j.epsr.2016.12.026   [Google Scholar]
  25. Poudel S, Ni Z, and Sun W (2018). Electrical distance approach for searching vulnerable branches during contingencies. IEEE Transactions on Smart Grid, 9(4): 3373-3382. https://doi.org/10.1109/TSG.2016.2631622   [Google Scholar]
  26. Sunitha R, Kumar RS, and Mathew AT (2013). Online static security assessment module using artificial neural networks. IEEE Transactions on Power Systems, 28(4): 4328-4335. https://doi.org/10.1109/TPWRS.2013.2267557   [Google Scholar]
  27. Torre DLS, Conejo AJ, and Contreras J (2008). Transmission expansion planning in electricity markets. IEEE Transactions on Power Systems, 23(1): 238-248. https://doi.org/10.1109/TPWRS.2007.913717   [Google Scholar]
  28. van Casteren JFL, Bollen MHJ, and Schmieg ME (2000). Reliability assessment in electrical power systems: The Weibull-Markov stochastic model. IEEE Transactions on Industry Applications, 36(3): 911-915. https://doi.org/10.1109/28.845070   [Google Scholar]