IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i11p2693-d363465.html
   My bibliography  Save this article

Research on the Hybrid Recommendation Method of Retail Electricity Price Package Based on Power User Characteristics and Multi-Attribute Utility in China

Author

Listed:
  • Yongxiu He

    (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, Beijing 102206, China)

  • Meiyan Wang

    (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, Beijing 102206, China)

  • Jinxiong Yu

    (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, Beijing 102206, China)

  • Qing He

    (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, Beijing 102206, China)

  • Huijun Sun

    (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, Beijing 102206, China)

  • Fengyu Su

    (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, Beijing 102206, China)

Abstract

With the deregulation of the retail electricity market and the increase of the types of electricity price packages, electricity retail companies provide the recommended service of price packages for users, so as to improve the market competitiveness and user stickiness of enterprises. The existing research does not fully consider the impact of user characteristics and package attributes on recommendation results. This paper proposes a hybrid recommendation method of retail electricity price package based on the characteristics of power users and the multi-attribute utility of price package. Firstly, the hierarchical model of hybrid characteristics of power users in retail electricity market is constructed based on the tree structure, and all characteristics are analyzed quantitatively by proximity measurement method. Then, based on the multi-attribute utility theory, the utility model of retail electricity price package to users is constructed. Secondly, the accurate recommendation of the package is realized according to the characteristics of power users and the multi-attribute utility of price package. Finally, the rationality of the hybrid recommendation method of the retail electricity price package is verified by empirical analysis. This study provides valuable support for user to choose the retail electricity price package and improve the competitiveness of power retail companies.

Suggested Citation

  • Yongxiu He & Meiyan Wang & Jinxiong Yu & Qing He & Huijun Sun & Fengyu Su, 2020. "Research on the Hybrid Recommendation Method of Retail Electricity Price Package Based on Power User Characteristics and Multi-Attribute Utility in China," Energies, MDPI, vol. 13(11), pages 1-18, May.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:11:p:2693-:d:363465
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/11/2693/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/11/2693/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Diego M. Jiménez-Bravo & Javier Pérez-Marcos & Daniel H. De la Iglesia & Gabriel Villarrubia González & Juan F. De Paz, 2019. "Multi-Agent Recommendation System for Electrical Energy Optimization and Cost Saving in Smart Homes," Energies, MDPI, vol. 12(7), pages 1-22, April.
    2. Prajwal Khadgi & Lihui Bai, 2018. "A simulation study for residential electricity user behavior under dynamic variable pricing with demand charge," IISE Transactions, Taylor & Francis Journals, vol. 50(8), pages 699-710, August.
    3. 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.
    4. Guang, Fengtao & He, Yongxiu & Wen, Le, 2019. "Impacts of hybrid time-varying tariffs on residential electricity demand: The case of Zhejiang Province," Utilities Policy, Elsevier, vol. 61(C).
    5. Bae, Mungyu & Kim, Hwantae & Kim, Eugene & Chung, Albert Yongjoon & Kim, Hwangnam & Roh, Jae Hyung, 2014. "Toward electricity retail competition: Survey and case study on technical infrastructure for advanced electricity market system," Applied Energy, Elsevier, vol. 133(C), pages 252-273.
    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. Yang, Yuyan & Xu, Xiao & Pan, Li & Liu, Junyong & Liu, Jichun & Hu, Weihao, 2024. "Distributed prosumer trading in the electricity and carbon markets considering user utility," Renewable Energy, Elsevier, vol. 228(C).

    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. 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.
    2. Yongxiu He & Meiyan Wang & Fengtao Guang, 2019. "Applicability Evaluation of China’s Retail Electricity Price Package Combining Data Envelopment Analysis and a Cloud Model," Energies, MDPI, vol. 13(1), pages 1-21, December.
    3. Zhang, Chonghui & Bai, Chen & Su, Weihua & Balezentis, Tomas, 2024. "The centralised data envelopment analysis model integrated with cost information and utility theory for power price setting under carbon peak strategy at the firm-level," Energy, Elsevier, vol. 292(C).
    4. Hartley, Peter R. & Medlock, Kenneth B. & Jankovska, Olivera, 2019. "Electricity reform and retail pricing in Texas," Energy Economics, Elsevier, vol. 80(C), pages 1-11.
    5. Bin Luo & Shumin Miao & Chuntian Cheng & Yi Lei & Gang Chen & Lang Gao, 2019. "Long-Term Generation Scheduling for Cascade Hydropower Plants Considering Price Correlation between Multiple Markets," Energies, MDPI, vol. 12(12), pages 1-17, June.
    6. Duojiao Tan & Bilal & Simon Gao & Bushra Komal, 2020. "Impact of Carbon Emission Trading System Participation and Level of Internal Control on Quality of Carbon Emission Disclosures: Insights from Chinese State-Owned Electricity Companies," Sustainability, MDPI, vol. 12(5), pages 1-14, February.
    7. Wei, Wei & Han, Ying & Abedin, Mohammad Zoynul & Ma, Jingjing & Chai, Shanglei, 2023. "Empirical study on the technical efficiency and total factor productivity of power industry: Evidence from Chinese provinces," Energy Economics, Elsevier, vol. 128(C).
    8. Asaad, Mohammad & Ahmad, Furkan & Alam, Mohammad Saad & Sarfraz, Mohammad, 2021. "Smart grid and Indian experience: A review," Resources Policy, Elsevier, vol. 74(C).
    9. Majidpour, Mostafa & Qiu, Charlie & Chu, Peter & Pota, Hemanshu R. & Gadh, Rajit, 2016. "Forecasting the EV charging load based on customer profile or station measurement?," Applied Energy, Elsevier, vol. 163(C), pages 134-141.
    10. Tsao, Yu-Chung & Thanh, Vo-Van & Lu, Jye-Chyi, 2022. "Efficiency of resilient three-part tariff pricing schemes in residential power markets," Energy, Elsevier, vol. 239(PD).
    11. Lin, Boqiang & Wu, Wei, 2017. "Cost of long distance electricity transmission in China," Energy Policy, Elsevier, vol. 109(C), pages 132-140.
    12. Zhongxiang Zhang, 2018. "Energy price reform in China," CCEP Working Papers 1805, Centre for Climate & Energy Policy, Crawford School of Public Policy, The Australian National University.
    13. Jin, Xiaolong & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Xu, Xiandong & Yu, Xiaodan, 2016. "Optimal day-ahead scheduling of integrated urban energy systems," Applied Energy, Elsevier, vol. 180(C), pages 1-13.
    14. Yabin Da & Bin Zeng & Jing-Li Fan & Jiawei Hu & Lanlan Li, 2023. "Heterogeneous responses to climate: evidence from residential electricity consumption," Climatic Change, Springer, vol. 176(8), pages 1-19, August.
    15. Ahmed, Tauqir & Bhatti, Arshad Ali, 2019. "Do power sector reforms affect electricity prices in selected Asian countries?," Energy Policy, Elsevier, vol. 129(C), pages 1253-1260.
    16. Ming, Zeng & Ping, Zhang & Shunkun, Yu & Hui, Liu, 2017. "Overall review of the overcapacity situation of China’s thermal power industry: Status quo, policy analysis and suggestions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 768-774.
    17. Jelena Lukić & Miloš Radenković & Marijana Despotović-Zrakić & Aleksandra Labus & Zorica Bogdanović, 2017. "Supply chain intelligence for electricity markets: A smart grid perspective," Information Systems Frontiers, Springer, vol. 19(1), pages 91-107, February.
    18. Jamil, Muhammad Hamza & Ullah, Kafait & Saleem, Noor & Abbas, Faisal & Khalid, Hassan Abdullah, 2022. "Did the restructuring of the electricity generation sector increase social welfare in Pakistan?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    19. Cheng, Chuntian & Chen, Fu & Li, Gang & Ristić, Bora & Mirchi, Ali & Qiyu, Tu & Madani, Kaveh, 2018. "Reform and renewables in China: The architecture of Yunnan's hydropower dominated electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 682-693.
    20. Li, Mingquan & Gao, Huiwen & Abdulla, Ahmed & Shan, Rui & Gao, Shuo, 2022. "Combined effects of carbon pricing and power market reform on CO2 emissions reduction in China's electricity sector," Energy, Elsevier, vol. 257(C).

    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:jeners:v:13:y:2020:i:11:p:2693-:d:363465. 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.