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Profit-seeking energy-intensive enterprises participating in power system scheduling: Model and mechanism

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  • Chen, Runze
  • Sun, Hongbin
  • Guo, Qinglai
  • Jin, Hongyang
  • Wu, Wenchuan
  • Zhang, Boming

Abstract

Energy-intensive enterprises (EIEs) are typical kinds of industrial loads. They consume large amounts of electricity, and are very sensitive to electricity prices. Moreover, they have very good schedulability: they own various adjustable devices and dispatchable self-owned generation units, and have great flexibility in making production decisions. The characteristics of EIEs make them potentially ideal for coordinating with power systems and gaining a win–win situation, especially when the renewable energy penetration rate is high. However, problems still remain as to how to organize this coordination. In this paper, we design a decomposed coordinative scheduling (DCS) approach in which independent EIEs and the system exchange information iteratively to achieve final settlements. Based on a general modeling of EIEs, we introduce a mathematical formulation for DCS. The corresponding algorithm is also provided. We compare DCS to other scheduling approaches in case studies. It shows that DCS can significantly improve the benefits of the two sides without harming the privacy of EIEs.

Suggested Citation

  • Chen, Runze & Sun, Hongbin & Guo, Qinglai & Jin, Hongyang & Wu, Wenchuan & Zhang, Boming, 2015. "Profit-seeking energy-intensive enterprises participating in power system scheduling: Model and mechanism," Applied Energy, Elsevier, vol. 158(C), pages 263-274.
    • Handle: RePEc:eee:appene:v:158:y:2015:i:c:p:263-274
    DOI: 10.1016/j.apenergy.2015.08.018
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    1. Guandalini, Giulio & Campanari, Stefano & Romano, Matteo C., 2015. "Power-to-gas plants and gas turbines for improved wind energy dispatchability: Energy and economic assessment," Applied Energy, Elsevier, vol. 147(C), pages 117-130.
    2. Ghadimi, P. & Kara, S. & Kornfeld, B., 2014. "The optimal selection of on-site CHP systems through integrated sizing and operational strategy," Applied Energy, Elsevier, vol. 126(C), pages 38-46.
    3. Wang, Yong & Li, Lin, 2015. "Time-of-use electricity pricing for industrial customers: A survey of U.S. utilities," Applied Energy, Elsevier, vol. 149(C), pages 89-103.
    4. Stötzer, Martin & Hauer, Ines & Richter, Marc & Styczynski, Zbigniew A., 2015. "Potential of demand side integration to maximize use of renewable energy sources in Germany," Applied Energy, Elsevier, vol. 146(C), pages 344-352.
    5. Paulus, Moritz & Borggrefe, Frieder, 2011. "The potential of demand-side management in energy-intensive industries for electricity markets in Germany," Applied Energy, Elsevier, vol. 88(2), pages 432-441, February.
    6. Middelberg, Arno & Zhang, Jiangfeng & Xia, Xiaohua, 2009. "An optimal control model for load shifting - With application in the energy management of a colliery," Applied Energy, Elsevier, vol. 86(7-8), pages 1266-1273, July.
    7. Finn, Paddy & Fitzpatrick, Colin, 2014. "Demand side management of industrial electricity consumption: Promoting the use of renewable energy through real-time pricing," Applied Energy, Elsevier, vol. 113(C), pages 11-21.
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    Cited by:

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    3. Liao, Siyang & Xu, Jian & Sun, Yuanzhang & Bao, Yi, 2018. "Local utilization of wind electricity in isolated power systems by employing coordinated control scheme of industrial energy-intensive load," Applied Energy, Elsevier, vol. 217(C), pages 14-24.
    4. Liu, Jia & Cheng, Haozhong & Zeng, Pingliang & Yao, Liangzhong & Shang, Ce & Tian, Yuan, 2018. "Decentralized stochastic optimization based planning of integrated transmission and distribution networks with distributed generation penetration," Applied Energy, Elsevier, vol. 220(C), pages 800-813.
    5. Dandan Zhu & Wenying Liu & Yang Hu & Weizhou Wang, 2018. "A Practical Load-Source Coordinative Method for Further Reducing Curtailed Wind Power in China with Energy-Intensive Loads," Energies, MDPI, vol. 11(11), pages 1-14, October.
    6. Jin, Hongyang & Li, Zhengshuo & Sun, Hongbin & Guo, Qinglai & Chen, Runze & Wang, Bin, 2017. "A robust aggregate model and the two-stage solution method to incorporate energy intensive enterprises in power system unit commitment," Applied Energy, Elsevier, vol. 206(C), pages 1364-1378.

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