IDEAS home Printed from https://ideas.repec.org/a/wut/journl/v4y2019p41-52id1473.html
   My bibliography  Save this article

A novel Data Envelopment Analysis model with complex numbers. Measuring the efficiency of generators in steam power plants

Author

Listed:
  • Mahmood Esfandiari
  • Saber Saati
  • Mehrzad Navabakhsh
  • Kaveh Khalili-Damghani

Abstract

The output of a generator in power plant is the electricity, and it consists of two parts, active and reactive power. These quantities are expressed as complex numbers in which the real part is the active power and the imaginary part is the reactive power. Reactive power plays an important role in an electricity network. Ignoring it will exclude a lot of information. With regard to the importance of the generators in power plants, surely, calculating the efficiency of these units is of great importance. Data Envelopment Analysis (DEA) is a nonparametric approach to measure the relative efficiency of Decision-Making Units (DMUs). Since the generators data are complex numbers, thus, if we the use classical DEA models in order to measure the efficiency of the generators in power plants, the reactive power cannot be considered, and the measurement is limited to the real number of electric power. In this paper, a new DEA model with complex numbers is developed in order to assess the performance of the power plant generators.

Suggested Citation

  • Mahmood Esfandiari & Saber Saati & Mehrzad Navabakhsh & Kaveh Khalili-Damghani, 2019. "A novel Data Envelopment Analysis model with complex numbers. Measuring the efficiency of generators in steam power plants," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 29(4), pages 41-52.
    • Handle: RePEc:wut:journl:v:4:y:2019:p:41-52:id:1473
    DOI: 10.37190/ord190403
    as

    Download full text from publisher

    File URL: https://ord.pwr.edu.pl/assets/papers_archive/1473%20-%20published.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.37190/ord190403?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
    ---><---

    References listed on IDEAS

    as
    1. M C A Silva Portela & E Thanassoulis & G Simpson, 2004. "Negative data in DEA: a directional distance approach applied to bank branches," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1111-1121, October.
    2. Park, Soo-Uk & Lesourd, Jean-Baptiste, 2000. "The efficiency of conventional fuel power plants in South Korea: A comparison of parametric and non-parametric approaches," International Journal of Production Economics, Elsevier, vol. 63(1), pages 59-67, January.
    3. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    4. Xiaohuan Lyu & Anna Shi, 2018. "Research on the Renewable Energy Industry Financing Efficiency Assessment and Mode Selection," Sustainability, MDPI, vol. 10(1), pages 1-13, January.
    5. Meilin Wen & Linhan Guo & Rui Kang & Yi Yang, 2014. "Data Envelopment Analysis with Uncertain Inputs and Outputs," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-7, August.
    6. Liu, C.H. & Lin, Sue J. & Lewis, Charles, 2010. "Evaluation of thermal power plant operational performance in Taiwan by data envelopment analysis," Energy Policy, Elsevier, vol. 38(2), pages 1049-1058, February.
    7. William W. Cooper & Kyung Sam Park & Gang Yu, 1999. "IDEA and AR-IDEA: Models for Dealing with Imprecise Data in DEA," Management Science, INFORMS, vol. 45(4), pages 597-607, April.
    8. Sarıca, Kemal & Or, Ilhan, 2007. "Efficiency assessment of Turkish power plants using data envelopment analysis," Energy, Elsevier, vol. 32(8), pages 1484-1499.
    9. Ya Chen & Yongjun Li & Qiwei Xie & Qingxian An & Liang Liang, 2014. "Data envelopment analysis with missing data: a multiple imputation approach," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 6(4), pages 315-337.
    10. Rajiv D. Banker, 1993. "Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation," Management Science, INFORMS, vol. 39(10), pages 1265-1273, October.
    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. Dorota Kuchta, 2023. "Project implementation scenario selection for sustainable project and product lifecycle management. Application of network data envelopment analysis," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 33(4), pages 133-154.

    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. Li, Feng & Zhang, Danlu & Zhang, Jinyu & Kou, Gang, 2022. "Measuring the energy production and utilization efficiency of Chinese thermal power industry with the fixed-sum carbon emission constraint," International Journal of Production Economics, Elsevier, vol. 252(C).
    2. Abdollah Hadi-Vencheh & Peter Wanke & Ali Jamshidi, 2020. "What Does Cost Structure Have to Say about Thermal Plant Energy Efficiency? The Case from Angola," Energies, MDPI, vol. 13(9), pages 1-25, May.
    3. Arabmaldar, Aliasghar & Sahoo, Biresh K. & Ghiyasi, Mojtaba, 2023. "A generalized robust data envelopment analysis model based on directional distance function," European Journal of Operational Research, Elsevier, vol. 311(2), pages 617-632.
    4. Mohammad Jamshidi & Masoud Sanei & Ali Mahmoodirad & Farhad Hoseinzadeh Lotfi & Ghasem Tohidi, 2021. "Uncertain SBM data envelopment analysis model: A case study in Iranian banks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2674-2689, April.
    5. Ogunrinde, Olawale & Shittu, Ekundayo, 2023. "Efficiency and productivity of renewable energy technologies: Evidence from U.S. investor-owned utilities across regional markets," Utilities Policy, Elsevier, vol. 82(C).
    6. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    7. Fallahi, Alireza & Ebrahimi, Reza & Ghaderi, S.F., 2011. "Measuring efficiency and productivity change in power electric generation management companies by using data envelopment analysis: A case study," Energy, Elsevier, vol. 36(11), pages 6398-6405.
    8. Lynes, Melissa & Featherstone, Allen, 2015. "Economic Efficiency of Utility Plants Under Renewable Energy Policy," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205674, Agricultural and Applied Economics Association.
    9. Liu, C.H. & Lin, Sue J. & Lewis, Charles, 2010. "Evaluation of thermal power plant operational performance in Taiwan by data envelopment analysis," Energy Policy, Elsevier, vol. 38(2), pages 1049-1058, February.
    10. Jindal, Abhinav & Nilakantan, Rahul, 2021. "Falling efficiency levels of Indian coal-fired power plants: A slacks-based analysis," Energy Economics, Elsevier, vol. 93(C).
    11. Gharneh, Naser Shams & Nabavieh, Alireza & Gholamiangonabadi, Davoud & Alimoradi, Mohammad, 2014. "Productivity change and its determinants: Application of the Malmquist index with bootstrapping in Iranian steam power plants," Utilities Policy, Elsevier, vol. 31(C), pages 114-120.
    12. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    13. Youchao Tan & Udaya Shetty & Ali Diabat & T. Pakkala, 2015. "Aggregate directional distance formulation of DEA with integer variables," Annals of Operations Research, Springer, vol. 235(1), pages 741-756, December.
    14. Zahra Mohmmad Nejad & Alireza Ghaffari-Hadigheh, 2018. "A novel DEA model based on uncertainty theory," Annals of Operations Research, Springer, vol. 264(1), pages 367-389, May.
    15. Kao, Chiang & Liu, Shiang-Tai, 2009. "Stochastic data envelopment analysis in measuring the efficiency of Taiwan commercial banks," European Journal of Operational Research, Elsevier, vol. 196(1), pages 312-322, July.
    16. W. Cooper & L. Seiford & K. Tone & J. Zhu, 2007. "Some models and measures for evaluating performances with DEA: past accomplishments and future prospects," Journal of Productivity Analysis, Springer, vol. 28(3), pages 151-163, December.
    17. Jahangoshai Rezaee, Mustafa & Moini, Alireza & Makui, Ahmad, 2012. "Operational and non-operational performance evaluation of thermal power plants in Iran: A game theory approach," Energy, Elsevier, vol. 38(1), pages 96-103.
    18. Simar, Léopold & Vanhems, Anne & Wilson, Paul W., 2012. "Statistical inference for DEA estimators of directional distances," European Journal of Operational Research, Elsevier, vol. 220(3), pages 853-864.
    19. Park, K. Sam, 2010. "Duality, efficiency computations and interpretations in imprecise DEA," European Journal of Operational Research, Elsevier, vol. 200(1), pages 289-296, January.
    20. Khoshnevisan, Benyamin & Shariati, Hanifreza Motamed & Rafiee, Shahin & Mousazadeh, Hossein, 2014. "Comparison of energy consumption and GHG emissions of open field and greenhouse strawberry production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 316-324.

    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:wut:journl:v:4:y:2019:p:41-52:id:1473. 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: Adam Kasperski (email available below). General contact details of provider: https://edirc.repec.org/data/iopwrpl.html .

    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.