IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v138y2017icp1042-1055.html
   My bibliography  Save this article

Risk assessment of power transmission network failures in a uniform pricing electricity market environment

Author

Listed:
  • Abdin, Islam
  • Li, Yan-Fu
  • Zio, Enrico

Abstract

This paper proposes a novel risk assessment method for power network failures considering a uniform-pricing market environment, different from previous risk assessment studies, which mainly emphasize technical consequences of the failures. In this type of market, dispatch infeasibilities caused by line failures are solved using a counter-trading mechanism where costs arise as a result of correcting the power dispatch. The risk index proposed takes into account these correction costs as well as the cost of the energy not served due to the failure, while considering an oligopolistic behavior of the generation companies. A 3-stage model is proposed to simulate the bidding behavior in the market, under different line failures scenarios. The risk index proposed and the method for its calculation are applied on an adapted IEEE 6-bus reliability test system. A sensitivity analysis is performed to investigate the sensitivity of the results with respect to the level of competitiveness of the generation companies, measured by the conjectured-price response parameter which is assumed to be exogenous in our study.

Suggested Citation

  • Abdin, Islam & Li, Yan-Fu & Zio, Enrico, 2017. "Risk assessment of power transmission network failures in a uniform pricing electricity market environment," Energy, Elsevier, vol. 138(C), pages 1042-1055.
    • Handle: RePEc:eee:energy:v:138:y:2017:i:c:p:1042-1055
    DOI: 10.1016/j.energy.2017.07.115
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544217311908
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2017.07.115?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dijk, Justin & Willems, Bert, 2011. "The effect of counter-trading on competition in electricity markets," Energy Policy, Elsevier, vol. 39(3), pages 1764-1773, March.
    2. Lo Prete, Chiara & Hobbs, Benjamin F. & Norman, Catherine S. & Cano-Andrade, Sergio & Fuentes, Alejandro & von Spakovsky, Michael R. & Mili, Lamine, 2012. "Sustainability and reliability assessment of microgrids in a regional electricity market," Energy, Elsevier, vol. 41(1), pages 192-202.
    3. Li, Yan-Fu & Zio, Enrico, 2012. "A multi-state model for the reliability assessment of a distributed generation system via universal generating function," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 28-36.
    4. Aghaei, Jamshid & Alizadeh, Mohammad-Iman & Siano, Pierluigi & Heidari, Alireza, 2016. "Contribution of emergency demand response programs in power system reliability," Energy, Elsevier, vol. 103(C), pages 688-696.
    5. Borges, Carmen Lucia Tancredo, 2012. "An overview of reliability models and methods for distribution systems with renewable energy distributed generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 4008-4015.
    6. Dockner, Engelbert J, 1992. "A Dynamic Theory of Conjectural Variations," Journal of Industrial Economics, Wiley Blackwell, vol. 40(4), pages 377-395, December.
    7. Lin, Jin & Cheng, Lin & Chang, Yao & Zhang, Kai & Shu, Bin & Liu, Guangyi, 2014. "Reliability based power systems planning and operation with wind power integration: A review to models, algorithms and applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 921-934.
    8. Zhang, Peng & Li, Wenyuan & Li, Sherwin & Wang, Yang & Xiao, Weidong, 2013. "Reliability assessment of photovoltaic power systems: Review of current status and future perspectives," Applied Energy, Elsevier, vol. 104(C), pages 822-833.
    9. Esmaeeli, Mostafa & Kazemi, Ahad & Shayanfar, Heidarali & Chicco, Gianfranco & Siano, Pierluigi, 2017. "Risk-based planning of the distribution network structure considering uncertainties in demand and cost of energy," Energy, Elsevier, vol. 119(C), pages 578-587.
    10. Roshanak Nateghi & Seth D. Guikema & Yue (Grace) Wu & C. Bayan Bruss, 2016. "Critical Assessment of the Foundations of Power Transmission and Distribution Reliability Metrics and Standards," Risk Analysis, John Wiley & Sons, vol. 36(1), pages 4-15, January.
    11. Rocchetta, R. & Li, Y.F. & Zio, E., 2015. "Risk assessment and risk-cost optimization of distributed power generation systems considering extreme weather conditions," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 47-61.
    12. Larsen, Peter H. & LaCommare, Kristina H. & Eto, Joseph H. & Sweeney, James L., 2016. "Recent trends in power system reliability and implications for evaluating future investments in resiliency," Energy, Elsevier, vol. 117(P1), pages 29-46.
    13. Božič, Dušan & Pantoš, Miloš, 2015. "Impact of electric-drive vehicles on power system reliability," Energy, Elsevier, vol. 83(C), pages 511-520.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Abadie, Luis Ma & Chamorro, José M., 2019. "Physical adequacy of a power generation system: The case of Spain in the long term," Energy, Elsevier, vol. 166(C), pages 637-652.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Adefarati, T. & Bansal, R.C., 2017. "Reliability assessment of distribution system with the integration of renewable distributed generation," Applied Energy, Elsevier, vol. 185(P1), pages 158-171.
    2. Zhou, P. & Jin, R.Y. & Fan, L.W., 2016. "Reliability and economic evaluation of power system with renewables: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 537-547.
    3. Chiacchio, Ferdinando & D’Urso, Diego & Famoso, Fabio & Brusca, Sebastian & Aizpurua, Jose Ignacio & Catterson, Victoria M., 2018. "On the use of dynamic reliability for an accurate modelling of renewable power plants," Energy, Elsevier, vol. 151(C), pages 605-621.
    4. Ferdinando Chiacchio & Fabio Famoso & Diego D’Urso & Sebastian Brusca & Jose Ignacio Aizpurua & Luca Cedola, 2018. "Dynamic Performance Evaluation of Photovoltaic Power Plant by Stochastic Hybrid Fault Tree Automaton Model," Energies, MDPI, vol. 11(2), pages 1-22, January.
    5. Jose L. López-Prado & Jorge I. Vélez & Guisselle A. Garcia-Llinás, 2020. "Reliability Evaluation in Distribution Networks with Microgrids: Review and Classification of the Literature," Energies, MDPI, vol. 13(23), pages 1-31, November.
    6. Eryilmaz, Serkan & Navarro, Jorge, 2022. "A decision theoretic framework for reliability-based optimal wind turbine selection," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    7. Hossain, Eklas & Roy, Shidhartho & Mohammad, Naeem & Nawar, Nafiu & Dipta, Debopriya Roy, 2021. "Metrics and enhancement strategies for grid resilience and reliability during natural disasters," Applied Energy, Elsevier, vol. 290(C).
    8. Escalera, Alberto & Hayes, Barry & Prodanović, Milan, 2018. "A survey of reliability assessment techniques for modern distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 344-357.
    9. Mena, Rodrigo & Hennebel, Martin & Li, Yan-Fu & Zio, Enrico, 2014. "Self-adaptable hierarchical clustering analysis and differential evolution for optimal integration of renewable distributed generation," Applied Energy, Elsevier, vol. 133(C), pages 388-402.
    10. Shang, Ce & Lin, Teng & Li, Canbing & Wang, Keyou & Ai, Qian, 2021. "Joining resilience and reliability evaluation against both weather and ageing causes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    11. Cao, Yijia & Wang, Xifan & Li, Yong & Tan, Yi & Xing, Jianbo & Fan, Ruixiang, 2016. "A comprehensive study on low-carbon impact of distributed generations on regional power grids: A case of Jiangxi provincial power grid in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 766-778.
    12. Eduardo Quiles & Carlos Roldán-Blay & Guillermo Escrivá-Escrivá & Carlos Roldán-Porta, 2020. "Accurate Sizing of Residential Stand-Alone Photovoltaic Systems Considering System Reliability," Sustainability, MDPI, vol. 12(3), pages 1-18, February.
    13. Mo, Hua-Dong & Li, Yan-Fu & Zio, Enrico, 2016. "A system-of-systems framework for the reliability analysis of distributed generation systems accounting for the impact of degraded communication networks," Applied Energy, Elsevier, vol. 183(C), pages 805-822.
    14. Juan A. Martinez-Velasco & Gerardo Guerra, 2016. "Reliability Analysis of Distribution Systems with Photovoltaic Generation Using a Power Flow Simulator and a Parallel Monte Carlo Approach," Energies, MDPI, vol. 9(7), pages 1-21, July.
    15. Mena, Rodrigo & Hennebel, Martin & Li, Yan-Fu & Zio, Enrico, 2016. "A multi-objective optimization framework for risk-controlled integration of renewable generation into electric power systems," Energy, Elsevier, vol. 106(C), pages 712-727.
    16. Hariri, Ali-Mohammad & Hashemi-Dezaki, Hamed & A. Hejazi, Maryam, 2020. "A novel generalized analytical reliability assessment method of smart grids including renewable and non-renewable distributed generations and plug-in hybrid electric vehicles," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    17. Peters, Lennart & Madlener, Reinhard, 2017. "Economic evaluation of maintenance strategies for ground-mounted solar photovoltaic plants," Applied Energy, Elsevier, vol. 199(C), pages 264-280.
    18. Müller, W. & Normann, H.T., 2003. "Conjectural Variations and Evolutionary Stability : A New Rationale for Consistency," Discussion Paper 2003-44, Tilburg University, Center for Economic Research.
    19. Engelbert Stockhammer & Paul Ramskogler, 2009. "Post-Keynesian economics How to move forward," European Journal of Economics and Economic Policies: Intervention, Edward Elgar Publishing, vol. 6(2), pages 227-246.
    20. Terracciano, Anthony Carmine & Vasu, Subith S. & Orlovskaya, Nina, 2016. "Design and development of a porous heterogeneous combustor for efficient heat production by combustion of liquid and gaseous fuels," Applied Energy, Elsevier, vol. 179(C), pages 228-236.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:138:y:2017:i:c:p:1042-1055. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.