IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i10p3635-d816577.html
   My bibliography  Save this article

Multi-Type Energy Demand Response Management Strategy Considering Energy Cascade Utilization

Author

Listed:
  • Jie Yu

    (School of Electricity Engineering, South East University, Nanjing 210000, China)

  • Yi Pan

    (School of Computer Science and Engineering, South East University, Suzhou 215000, China)

  • Juewei Wu

    (Nari Company, Nanjing 210000, China)

  • Yang Li

    (School of Electricity Engineering, South East University, Nanjing 210000, China)

Abstract

Using cascade utilization between multiple energy sources to realize multi-energy complementarity can significantly improve the economic benefits and energy utilization of integrated energy service providers. Integrated energy service providers consider the cascade utilization of energy in the regional energy system. Through the demand response management of user power loads and different qualities of heat energy, the energy loss of the system can be reduced and the energy utilization efficiency of the system can be further improved. In this paper, we creatively establish a multi-objective optimization model with the goal of a minimum total cost and minimum exergy loss, considering cross elasticity, which is solved with the constraints of equipment operation and the energy balance in the region. The calculation example proves that the implementation of energy cascade utilization and demand response management for different users, by integrated energy service providers, can effectively reduce the system cost and improve exergy efficiency, so as to realize the optimal management of economic utilization and energy value.

Suggested Citation

  • Jie Yu & Yi Pan & Juewei Wu & Yang Li, 2022. "Multi-Type Energy Demand Response Management Strategy Considering Energy Cascade Utilization," Energies, MDPI, vol. 15(10), pages 1-24, May.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:10:p:3635-:d:816577
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/10/3635/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/10/3635/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Liu, Yingqi, 2017. "Demand response and energy efficiency in the capacity resource procurement: Case studies of forward capacity markets in ISO New England, PJM and Great Britain," Energy Policy, Elsevier, vol. 100(C), pages 271-282.
    Full references (including those not matched with items on IDEAS)

    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. Meyabadi, A. Fattahi & Deihimi, M.H., 2017. "A review of demand-side management: Reconsidering theoretical framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 367-379.
    2. Lu, Qing & Yu, Hao & Zhao, Kangli & Leng, Yajun & Hou, Jianchao & Xie, Pinjie, 2019. "Residential demand response considering distributed PV consumption: A model based on China's PV policy," Energy, Elsevier, vol. 172(C), pages 443-456.
    3. Ito, Masakazu & Takano, Akihisa & Shinji, Takao & Yagi, Takahiro & Hayashi, Yasuhiro, 2017. "Electricity adjustment for capacity market auction by a district heating and cooling system," Applied Energy, Elsevier, vol. 206(C), pages 623-633.
    4. Srđan Skok & Ahmed Mutapčić & Renata Rubesa & Mario Bazina, 2020. "Transmission Power System Modeling by Using Aggregated Distributed Generation Model Based on a TSO—DSO Data Exchange Scheme," Energies, MDPI, vol. 13(15), pages 1-15, August.
    5. Yilmaz, S. & Rinaldi, A. & Patel, M.K., 2020. "DSM interactions: What is the impact of appliance energy efficiency measures on the demand response (peak load management)?," Energy Policy, Elsevier, vol. 139(C).
    6. Jun Dong & Rong Li & Hui Huang, 2018. "Performance Evaluation of Residential Demand Response Based on a Modified Fuzzy VIKOR and Scalable Computing Method," Energies, MDPI, vol. 11(5), pages 1-27, April.
    7. Chu, Wenfeng & Zhang, Yu & Wang, Donglin & He, Wei & Zhang, Sheng & Hu, Zhongting & Zhou, Jinzhi, 2023. "Capacity determination of renewable energy systems, electricity storage, and heat storage in grid-interactive buildings," Energy, Elsevier, vol. 285(C).
    8. Banshwar, Anuj & Sharma, Naveen Kumar & Sood, Yog Raj & Shrivastava, Rajnish, 2018. "An international experience of technical and economic aspects of ancillary services in deregulated power industry: Lessons for emerging BRIC electricity markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 774-801.
    9. Muñoz, Juan C. & Sauma, Enzo & Muñoz, Francisco D. & Moreno, Rodrigo, 2023. "Analysis of generation investments under price controls in cross-border trade of electricity," Energy Economics, Elsevier, vol. 123(C).
    10. Eduardo J. Salazar & Mauro Jurado & Mauricio E. Samper, 2023. "Reinforcement Learning-Based Pricing and Incentive Strategy for Demand Response in Smart Grids," Energies, MDPI, vol. 16(3), pages 1-33, February.
    11. Luo, Na & Langevin, Jared & Chandra-Putra, Handi & Lee, Sang Hoon, 2022. "Quantifying the effect of multiple load flexibility strategies on commercial building electricity demand and services via surrogate modeling," Applied Energy, Elsevier, vol. 309(C).
    12. Zhang, Yuanyuan & Zhao, Huiru & Li, Bingkang, 2022. "Research on the design and influence of unit generation capacity adequacy guarantee mechanism in the power market," Energy, Elsevier, vol. 248(C).
    13. Erik Heilmann & Nikolai Klempp & Kai Hufendiek & Heike Wetzel, 2022. "Long-term Contracts for Network-supportive Flexibility in Local Flexibility Markets," MAGKS Papers on Economics 202224, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    14. Leinauer, Christina & Schott, Paul & Fridgen, Gilbert & Keller, Robert & Ollig, Philipp & Weibelzahl, Martin, 2022. "Obstacles to demand response: Why industrial companies do not adapt their power consumption to volatile power generation," Energy Policy, Elsevier, vol. 165(C).
    15. Chen, Yongbao & Zhang, Lixin & Xu, Peng & Di Gangi, Alessandra, 2021. "Electricity demand response schemes in China: Pilot study and future outlook," Energy, Elsevier, vol. 224(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:15:y:2022:i:10:p:3635-:d:816577. 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.