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Optimizing Load Dispatch in Iron and Steel Enterprises Aligns with Solar Power Generation and Achieves Low-Carbon Goals

Author

Listed:
  • Samrawit Bzayene Fesseha

    (School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Bin Li

    (School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Bing Qi

    (School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Songsong Chen

    (Beijing Key Laboratory of Demand Side Multi-Energy Complementary Optimization and Supply-Demand Interaction Technology, China Electric Power Research Institute Co., Ltd., Beijing 100035, China)

  • Feixiang Gong

    (Beijing Key Laboratory of Demand Side Multi-Energy Complementary Optimization and Supply-Demand Interaction Technology, China Electric Power Research Institute Co., Ltd., Beijing 100035, China)

Abstract

This study develops an optimization-based scheduling framework for coordinating the energy-intensive operations of a steel enterprise with estimated solar power availability. Unlike prior approaches that focus primarily on process efficiency or carbon reduction in isolation, the proposed model integrates demand response with linear programming to improve solar utilization while respecting load priorities. The solar generation profile is derived from typical meteorological year (TMY) irradiance data, adjusted for panel efficiency and system parameters, thereby serving as an estimated input rather than measured data. Simulation results over a 31-day horizon show that coordinated scheduling can reduce grid dependence and increase solar energy utilization by up to 99% under the simulated conditions. While the findings demonstrate the potential of load scheduling for industrial decarbonization, they are based on estimated solar data and a simplified system representation. Future work should incorporate real-world solar measurements and stochastic models to address uncertainty and further validate industrial applicability.

Suggested Citation

  • Samrawit Bzayene Fesseha & Bin Li & Bing Qi & Songsong Chen & Feixiang Gong, 2025. "Optimizing Load Dispatch in Iron and Steel Enterprises Aligns with Solar Power Generation and Achieves Low-Carbon Goals," Energies, MDPI, vol. 18(17), pages 1-15, September.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:17:p:4662-:d:1740636
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    References listed on IDEAS

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    1. Andrade, Carlos & Desport, Lucas & Selosse, Sandrine, 2024. "Net-negative emission opportunities for the iron and steel industry on a global scale," Applied Energy, Elsevier, vol. 358(C).
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