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Source-Load Collaborative Optimization Method Considering Core Production Constraints of Electrolytic Aluminum Load

Author

Listed:
  • Yibo Jiang

    (State Grid (Suzhou) City & Energy Research Institute, Suzhou 215000, China)

  • Zhe Wang

    (State Grid (Suzhou) City & Energy Research Institute, Suzhou 215000, China)

  • Shiqi Bian

    (School of Electrical and Automation, Wuhan University, Wuhan 430072, China)

  • Siyang Liao

    (School of Electrical and Automation, Wuhan University, Wuhan 430072, China)

  • Huibin Lu

    (State Grid (Suzhou) City & Energy Research Institute, Suzhou 215000, China)

Abstract

With the deep implementation of the national “dual carbon” strategy, the development of a new power system dominated by renewable energy has accelerated significantly. Electrolytic aluminum load, as an important energy-intensive industrial resource, possesses response flexibility, providing a critical pathway for the efficient utilization of renewable energy. However, ensuring the safety of its production process during demand-side response remains a key challenge. This study systematically investigates the core production constraint of electrolytic aluminum load—electrolytic bath temperature—and its impacts on chemical reaction rates, current efficiency, and production equipment. A detailed coupling relationship between core production constraints and active power regulation is established. By quantifying the effects of temperature variation on the electrolytic aluminum production process, a demand-side response control cost model for electrolytic aluminum load is proposed. Additionally, a day-ahead scheduling model is developed with the objective of minimizing system operating costs while considering the participation of electrolytic aluminum load. Simulation results demonstrate that this method significantly reduces wind curtailment and load shedding while ensuring the safety of electrolytic aluminum production. It provides a novel approach for enhancing system economic efficiency, improving renewable energy utilization, and promoting the deep integration of power systems with industrial loads.

Suggested Citation

  • Yibo Jiang & Zhe Wang & Shiqi Bian & Siyang Liao & Huibin Lu, 2024. "Source-Load Collaborative Optimization Method Considering Core Production Constraints of Electrolytic Aluminum Load," Energies, MDPI, vol. 17(24), pages 1-17, December.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:24:p:6396-:d:1547602
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    References listed on IDEAS

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    1. Yang, Hongming & Liang, Rui & Yuan, Yuan & Chen, Bowen & Xiang, Sheng & Liu, Junpeng & Zhao, Huan & Ackom, Emmanuel, 2022. "Distributionally robust optimal dispatch in the power system with high penetration of wind power based on net load fluctuation data," Applied Energy, Elsevier, vol. 313(C).
    2. Yue, Xiaoyu & Liao, Siyang & Xu, Jian & Ke, Deping & Wang, Huiji & Yang, Jiaquan & He, Xuehao, 2024. "Collaborative optimization of renewable energy power systems integrating electrolytic aluminum load regulation and thermal power deep peak shaving," Applied Energy, Elsevier, vol. 373(C).
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