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Planning and Scheduling for Industrial Demand-Side Management: State of the Art, Opportunities and Challenges under Integration of Energy Internet and Industrial Internet

Author

Listed:
  • Songsong Chen

    (China Electric Power Research Institute, Beijing 100192, China)

  • Feixiang Gong

    (China Electric Power Research Institute, Beijing 100192, China)

  • Mingqiang Zhang

    (School of Electrical Engineering and Automation, Wuhan University, Wuhan 430000, China)

  • Jindou Yuan

    (China Electric Power Research Institute, Beijing 100192, China)

  • Siyang Liao

    (School of Electrical Engineering and Automation, Wuhan University, Wuhan 430000, China)

  • Hongyin Chen

    (China Electric Power Research Institute, Beijing 100192, China)

  • Dezhi Li

    (China Electric Power Research Institute, Beijing 100192, China)

  • Shiming Tian

    (China Electric Power Research Institute, Beijing 100192, China)

  • Xiaojian Hu

    (China Electric Power Research Institute, Beijing 100192, China)

Abstract

Industrial power has a large load base and considerable adjustment potential. Enterprises with a high degree of automation and adjustable potential can automatically adjust the production status according to the peak load, frequency of the power grid and the demand of new energy consumption, so as to realize automatic demand response. This paper analyzes the opportunities and challenges of industrial demand response under the integration of Industrial Internet and Energy Internet. At the same time, the development direction of industrial demand response under the new situation, such as comprehensive demand response, adjustable load resources and other technical and policy aspects are prospected.

Suggested Citation

  • Songsong Chen & Feixiang Gong & Mingqiang Zhang & Jindou Yuan & Siyang Liao & Hongyin Chen & Dezhi Li & Shiming Tian & Xiaojian Hu, 2021. "Planning and Scheduling for Industrial Demand-Side Management: State of the Art, Opportunities and Challenges under Integration of Energy Internet and Industrial Internet," Sustainability, MDPI, vol. 13(14), pages 1-18, July.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:14:p:7753-:d:592557
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    References listed on IDEAS

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    1. Helin, Kristo & Käki, Anssi & Zakeri, Behnam & Lahdelma, Risto & Syri, Sanna, 2017. "Economic potential of industrial demand side management in pulp and paper industry," Energy, Elsevier, vol. 141(C), pages 1681-1694.
    2. Arjuna Nebel & Christine Krüger & Tomke Janßen & Mathieu Saurat & Sebastian Kiefer & Karin Arnold, 2020. "Comparison of the Effects of Industrial Demand Side Management and Other Flexibilities on the Performance of the Energy System," Energies, MDPI, vol. 13(17), pages 1-20, August.
    3. Levy, Roger, 2006. "A Vision of Demand Response - 2016," The Electricity Journal, Elsevier, vol. 19(8), pages 12-23, October.
    4. Zhou, Kaile & Yang, Shanlin & Shao, Zhen, 2016. "Energy Internet: The business perspective," Applied Energy, Elsevier, vol. 178(C), pages 212-222.
    5. Drexl, A. & Kimms, A., 1997. "Lot sizing and scheduling -- Survey and extensions," European Journal of Operational Research, Elsevier, vol. 99(2), pages 221-235, June.
    6. Bao, Yi & Xu, Jian & Feng, Wei & Sun, Yuanzhang & Liao, Siyang & Yin, Rongxin & Jiang, Yazhou & Jin, Ming & Marnay, Chris, 2019. "Provision of secondary frequency regulation by coordinated dispatch of industrial loads and thermal power plants," Applied Energy, Elsevier, vol. 241(C), pages 302-312.
    7. Mao, Kun & Pan, Quan-ke & Pang, Xinfu & Chai, Tianyou, 2014. "A novel Lagrangian relaxation approach for a hybrid flowshop scheduling problem in the steelmaking-continuous casting process," European Journal of Operational Research, Elsevier, vol. 236(1), pages 51-60.
    8. Zhili Zhou & Yongpei Guan, 2013. "Two-stage stochastic lot-sizing problem under cost uncertainty," Annals of Operations Research, Springer, vol. 209(1), pages 207-230, October.
    9. Archetti, Claudia & Bertazzi, Luca & Grazia Speranza, M., 2014. "Polynomial cases of the economic lot sizing problem with cost discounts," European Journal of Operational Research, Elsevier, vol. 237(2), pages 519-527.
    10. Yevgenia Mikhaylidi & Hussein Naseraldin & Liron Yedidsion, 2015. "Operations scheduling under electricity time-varying prices," International Journal of Production Research, Taylor & Francis Journals, vol. 53(23), pages 7136-7157, December.
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