IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i7p2130-d153866.html
   My bibliography  Save this article

Comprehensive Performance Evaluation of Electricity Grid Corporations Employing a Novel MCDM Model

Author

Listed:
  • Haoran Zhao

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Changping, Beijing 102206, China)

  • Huiru Zhao

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Changping, Beijing 102206, China)

  • Sen Guo

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Changping, Beijing 102206, China)

Abstract

Under the new round reform of electricity market in China, a large amount of electricity sales companies has emerged in some provinces, and the reform of transmission and distribution tariffs is also in progress. Electricity grid corporations are required to update their operational strategies and improve comprehensive performance to adapt to the fierce competition in the electricity market. Considering this, a novel MCDM (multi-criteria decision making) model integrating Fuzzy-Delphi, the best-worst method (BWM), the entropy weight calculation approach, and the VIKOR method is established in this investigation to assess the comprehensive performances of five selected provincial electricity grid corporations. The comprehensive performance assessment indicator system is constructed in accordance with Fuzzy-Delphi approach, composed of 21 significant sub-criteria from the aspects of profitability capacity, development capacity, safety production capacity, electricity supply reliability, outstanding service provision, energy conservation, and environmental protection. The sub-criteria weights are computed by combining subjective weights determined by BWM and objective weights computed by the entropy weight calculation approach. The comprehensive performance evaluation model is established based on VIKOR. As the electricity grid corporation A is superior in profitability capacity (especially in electricity sales amount) and safety production capacity criterion, it is superior over other four electricity grid corporations. The established novel MCDM is practical and rational, which is applicable for electricity grid corporations’ comprehensive performance evaluation.

Suggested Citation

  • Haoran Zhao & Huiru Zhao & Sen Guo, 2018. "Comprehensive Performance Evaluation of Electricity Grid Corporations Employing a Novel MCDM Model," Sustainability, MDPI, vol. 10(7), pages 1-23, June.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:7:p:2130-:d:153866
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/7/2130/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/10/7/2130/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. You, Yan Q. & Jie, Tao, 2016. "A study of the operation efficiency and cost performance indices of power-supply companies in China based on a dynamic network slacks-based measure model," Omega, Elsevier, vol. 60(C), pages 85-97.
    2. Gupta, Himanshu, 2018. "Evaluating service quality of airline industry using hybrid best worst method and VIKOR," Journal of Air Transport Management, Elsevier, vol. 68(C), pages 35-47.
    3. Nastaran Chitsaz & Ali Azarnivand, 2017. "Water Scarcity Management in Arid Regions Based on an Extended Multiple Criteria Technique," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(1), pages 233-250, January.
    4. Kumar, Abhishek & Sah, Bikash & Singh, Arvind R. & Deng, Yan & He, Xiangning & Kumar, Praveen & Bansal, R.C., 2017. "A review of multi criteria decision making (MCDM) towards sustainable renewable energy development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 596-609.
    5. Zeng, Ming & Yang, Yongqi & Wang, Lihua & Sun, Jinghui, 2016. "The power industry reform in China 2015: Policies, evaluations and solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 94-110.
    6. Latinopoulos, D. & Kechagia, K., 2015. "A GIS-based multi-criteria evaluation for wind farm site selection. A regional scale application in Greece," Renewable Energy, Elsevier, vol. 78(C), pages 550-560.
    7. Peipei You & Sen Guo & Haoran Zhao & Huiru Zhao, 2017. "Operation Performance Evaluation of Power Grid Enterprise Using a Hybrid BWM-TOPSIS Method," Sustainability, MDPI, vol. 9(12), pages 1-15, December.
    8. Qingyong Wang & Hong-Ning Dai & Hao Wang, 2017. "A Smart MCDM Framework to Evaluate the Impact of Air Pollution on City Sustainability: A Case Study from China," Sustainability, MDPI, vol. 9(6), pages 1-17, May.
    9. Salimi, Negin & Rezaei, Jafar, 2018. "Evaluating firms’ R&D performance using best worst method," Evaluation and Program Planning, Elsevier, vol. 66(C), pages 147-155.
    10. Simone Di Zio & Mara Maretti, 2014. "Acceptability of energy sources using an integration of the Delphi method and the analytic hierarchy process," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(6), pages 2973-2991, November.
    11. Shiu, Alice & Lam, Pun-Lee, 2004. "Electricity consumption and economic growth in China," Energy Policy, Elsevier, vol. 32(1), pages 47-54, January.
    12. Shuyu Dai & Dongxiao Niu, 2017. "Comprehensive Evaluation of the Sustainable Development of Power Grid Enterprises Based on the Model of Fuzzy Group Ideal Point Method and Combination Weighting Method with Improved Group Order Relati," Sustainability, MDPI, vol. 9(10), pages 1-22, October.
    13. Zheng, Yanan & Hu, Zhaoguang & Wang, Jianhui & Wen, Quan, 2014. "IRSP (integrated resource strategic planning) with interconnected smart grids in integrating renewable energy and implementing DSM (demand side management) in China," Energy, Elsevier, vol. 76(C), pages 863-874.
    14. Sun, Wei & Xu, Yanfeng, 2016. "Financial security evaluation of the electric power industry in China based on a back propagation neural network optimized by genetic algorithm," Energy, Elsevier, vol. 101(C), pages 366-379.
    15. Zhang, Sufang & Jiao, Yiqian & Chen, Wenjun, 2017. "Demand-side management (DSM) in the context of China's on-going power sector reform," Energy Policy, Elsevier, vol. 100(C), pages 1-8.
    16. Ren, Jingzheng & Liang, Hanwei & Chan, Felix T.S., 2017. "Urban sewage sludge, sustainability, and transition for Eco-City: Multi-criteria sustainability assessment of technologies based on best-worst method," Technological Forecasting and Social Change, Elsevier, vol. 116(C), pages 29-39.
    17. Sánchez-Lozano, J.M. & García-Cascales, M.S. & Lamata, M.T., 2016. "GIS-based onshore wind farm site selection using Fuzzy Multi-Criteria Decision Making methods. Evaluating the case of Southeastern Spain," Applied Energy, Elsevier, vol. 171(C), pages 86-102.
    18. Rezaei, Jafar, 2016. "Best-worst multi-criteria decision-making method: Some properties and a linear model," Omega, Elsevier, vol. 64(C), pages 126-130.
    19. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    20. Çolak, Murat & Kaya, İhsan, 2017. "Prioritization of renewable energy alternatives by using an integrated fuzzy MCDM model: A real case application for Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 840-853.
    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. Maghsoud Amiri & Mohammad Hashemi-Tabatabaei & Mohammad Ghahremanloo & Mehdi Keshavarz-Ghorabaee & Edmundas Kazimieras Zavadskas & Arturas Kaklauskas, 2021. "Evaluating Life Cycle of Buildings Using an Integrated Approach Based on Quantitative-Qualitative and Simplified Best-Worst Methods (QQM-SBWM)," Sustainability, MDPI, vol. 13(8), pages 1-28, April.
    2. Sen Guo & Wenyue Zhang & Xiao Gao, 2020. "Business Risk Evaluation of Electricity Retail Company in China Using a Hybrid MCDM Method," Sustainability, MDPI, vol. 12(5), pages 1-21, March.
    3. Yigit Kazancoglu & Yalcin Berberoglu & Cisem Lafci & Oleksander Generalov & Denys Solohub & Viktor Koval, 2023. "Environmental Sustainability Implications and Economic Prosperity of Integrated Renewable Solutions in Urban Development," Energies, MDPI, vol. 16(24), pages 1-24, December.
    4. Mu-Hsin Chang & James J. H. Liou & Huai-Wei Lo, 2019. "A Hybrid MCDM Model for Evaluating Strategic Alliance Partners in the Green Biopharmaceutical Industry," Sustainability, MDPI, vol. 11(15), pages 1-20, July.
    5. Yongli Wang & Shanshan Song & Mingchen Gao & Jingyan Wang & Jinrong Zhu & Zhongfu Tan, 2020. "Accounting for the Life Cycle Cost of Power Grid Projects by Employing a System Dynamics Technique: A Power Reform Perspective," Sustainability, MDPI, vol. 12(8), pages 1-28, April.
    6. Mi, Xiaomei & Tang, Ming & Liao, Huchang & Shen, Wenjing & Lev, Benjamin, 2019. "The state-of-the-art survey on integrations and applications of the best worst method in decision making: Why, what, what for and what's next?," Omega, Elsevier, vol. 87(C), pages 205-225.
    7. Jun Dong & Dongxue Wang & Dongran Liu & Palidan Ainiwaer & Linpeng Nie, 2019. "Operation Health Assessment of Power Market Based on Improved Matter-Element Extension Cloud Model," Sustainability, MDPI, vol. 11(19), pages 1-25, October.
    8. Rujee Rodcha & Nitin K. Tripathi & Rajendra Prasad Shrestha, 2019. "Comparison of Cash Crop Suitability Assessment Using Parametric, AHP, and FAHP Methods," Land, MDPI, vol. 8(5), pages 1-22, May.
    9. Yana Duan & Yang Sun & Yu Zhang & Xiaoqi Fan & Qinghuan Dong & Sen Guo, 2021. "Risk Evaluation of Electric Power Grid Investment in China Employing a Hybrid Novel MCDM Method," Mathematics, MDPI, vol. 9(5), pages 1-22, February.

    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. Peipei You & Sen Guo & Haoran Zhao & Huiru Zhao, 2017. "Operation Performance Evaluation of Power Grid Enterprise Using a Hybrid BWM-TOPSIS Method," Sustainability, MDPI, vol. 9(12), pages 1-15, December.
    2. Mi, Xiaomei & Tang, Ming & Liao, Huchang & Shen, Wenjing & Lev, Benjamin, 2019. "The state-of-the-art survey on integrations and applications of the best worst method in decision making: Why, what, what for and what's next?," Omega, Elsevier, vol. 87(C), pages 205-225.
    3. Haoran Zhao & Sen Guo & Huiru Zhao, 2018. "Selecting the Optimal Micro-Grid Planning Program Using a Novel Multi-Criteria Decision Making Model Based on Grey Cumulative Prospect Theory," Energies, MDPI, vol. 11(7), pages 1-24, July.
    4. Mališa Žižović & Dragan Pamučar & Goran Ćirović & Miodrag M. Žižović & Boža D. Miljković, 2020. "A Model for Determining Weight Coefficients by Forming a Non-Decreasing Series at Criteria Significance Levels (NDSL)," Mathematics, MDPI, vol. 8(5), pages 1-18, May.
    5. Sen Guo & Wenyue Zhang & Xiao Gao, 2020. "Business Risk Evaluation of Electricity Retail Company in China Using a Hybrid MCDM Method," Sustainability, MDPI, vol. 12(5), pages 1-21, March.
    6. Elkadeem, M.R. & Younes, Ali & Sharshir, Swellam W. & Campana, Pietro Elia & Wang, Shaorong, 2021. "Sustainable siting and design optimization of hybrid renewable energy system: A geospatial multi-criteria analysis," Applied Energy, Elsevier, vol. 295(C).
    7. Penjani Hopkins Nyimbili & Turan Erden, 2021. "Comparative evaluation of GIS-based best–worst method (BWM) for emergency facility planning: perspectives from two decision-maker groups," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(1), pages 1031-1067, January.
    8. Shih-Chia Chang & Ming-Tsang Lu & Mei-Jen Chen & Li-Hua Huang, 2021. "Evaluating the Application of CSR in the High-Tech Industry during the COVID-19 Pandemic," Mathematics, MDPI, vol. 9(15), pages 1-16, July.
    9. Maghsoud Amiri & Mohammad Hashemi-Tabatabaei & Mohammad Ghahremanloo & Mehdi Keshavarz-Ghorabaee & Edmundas Kazimieras Zavadskas & Arturas Kaklauskas, 2021. "Evaluating Life Cycle of Buildings Using an Integrated Approach Based on Quantitative-Qualitative and Simplified Best-Worst Methods (QQM-SBWM)," Sustainability, MDPI, vol. 13(8), pages 1-28, April.
    10. Dragan Pamučar & Ljubomir Gigović & Zoran Bajić & Miljojko Janošević, 2017. "Location Selection for Wind Farms Using GIS Multi-Criteria Hybrid Model: An Approach Based on Fuzzy and Rough Numbers," Sustainability, MDPI, vol. 9(8), pages 1-23, July.
    11. van de Kaa, Geerten & Janssen, Marijn & Rezaei, Jafar, 2018. "Standards battles for business-to-government data exchange: Identifying success factors for standard dominance using the Best Worst Method," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 182-189.
    12. Yasir Ahmed Solangi & Qingmei Tan & Muhammad Waris Ali Khan & Nayyar Hussain Mirjat & Ifzal Ahmed, 2018. "The Selection of Wind Power Project Location in the Southeastern Corridor of Pakistan: A Factor Analysis, AHP, and Fuzzy-TOPSIS Application," Energies, MDPI, vol. 11(8), pages 1-26, July.
    13. Bartłomiej Kizielewicz & Jarosław Wątróbski & Wojciech Sałabun, 2020. "Identification of Relevant Criteria Set in the MCDA Process—Wind Farm Location Case Study," Energies, MDPI, vol. 13(24), pages 1-40, December.
    14. Milad Kolagar & Seyed Mohammad Hassan Hosseini & Ramin Felegari & Parviz Fattahi, 2020. "Policy-making for renewable energy sources in search of sustainable development: a hybrid DEA-FBWM approach," Environment Systems and Decisions, Springer, vol. 40(4), pages 485-509, December.
    15. Dragan Pamučar & Fatih Ecer & Goran Cirovic & Melfi A. Arlasheedi, 2020. "Application of Improved Best Worst Method (BWM) in Real-World Problems," Mathematics, MDPI, vol. 8(8), pages 1-19, August.
    16. Jairo Ortega & Sarbast Moslem & János Tóth & Tamás Péter & Juan Palaguachi & Mario Paguay, 2020. "Using Best Worst Method for Sustainable Park and Ride Facility Location," Sustainability, MDPI, vol. 12(23), pages 1-18, December.
    17. Vineet Kaushik & Ashwani Kumar & Himanshu Gupta & Gaurav Dixit, 2022. "Modelling and prioritizing the factors for online apparel return using BWM approach," Electronic Commerce Research, Springer, vol. 22(3), pages 843-873, September.
    18. van de Kaa, G. & Fens, T. & Rezaei, J. & Kaynak, D. & Hatun, Z. & Tsilimeni-Archangelidi, A., 2019. "Realizing smart meter connectivity: Analyzing the competing technologies Power line communication, mobile telephony, and radio frequency using the best worst method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 320-327.
    19. Jian Wang & Jin-Chun Huang & Shan-Lin Huang & Gwo-Hshiung Tzeng & Ting Zhu, 2021. "Improvement Path for Resource-Constrained Cities Identified Using an Environmental Co-Governance Assessment Framework Based on BWM-mV Model," IJERPH, MDPI, vol. 18(9), pages 1-30, May.
    20. Geerten Van de Kaa & Daniel Scholten & Jafar Rezaei & Christine Milchram, 2017. "The Battle between Battery and Fuel Cell Powered Electric Vehicles: A BWM Approach," Energies, MDPI, vol. 10(11), pages 1-13, October.

    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:gam:jsusta:v:10:y:2018:i:7:p:2130-:d:153866. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.