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Stochastic Capacity Optimization of an Integrated BFGCC–MSHS–Wind–Solar Energy System for the Decarbonization of a Steelmaking Plant

Author

Listed:
  • Chamin Geng

    (Jiangsu Frontier Electric Technology Co., Ltd., Nanjing 211102, China)

  • Zhuoyue Shi

    (National Engineering Research Center of Power Generation Control and Safety, School of Energy and Environment, Southeast University, Nanjing 210096, China)

  • Xianhao Chen

    (National Engineering Research Center of Power Generation Control and Safety, School of Energy and Environment, Southeast University, Nanjing 210096, China)

  • Ziwen Sun

    (Jiangsu Frontier Electric Technology Co., Ltd., Nanjing 211102, China)

  • Yawei Jin

    (Jiangsu Frontier Electric Technology Co., Ltd., Nanjing 211102, China)

  • Tian Shi

    (Jiangsu Frontier Electric Technology Co., Ltd., Nanjing 211102, China)

  • Xiao Wu

    (National Engineering Research Center of Power Generation Control and Safety, School of Energy and Environment, Southeast University, Nanjing 210096, China)

Abstract

Deploying renewable generation to replace conventional fossil-fuel-based energy supplies provides an important pathway for the decarbonization of steelmaking plants. Meanwhile, it is also crucial to improve the flexibility of blast-furnace-gas-fired combined-cycle power plants (BFGCCs) to ease the accommodation of uncertain renewable generation. To this end, this paper proposes the deployment of a molten salt heat storage (MSHS) system in BFGCCs to store the heat of gas turbine flue gas so that the power–heat coupling of these BFGCCs can be unlocked to enhance the flexibility of the energy supply. A stochastic capacity optimization of an integrated BFGCC–MSHS–wind–solar (BMWS) energy system is presented to determine the optimal installed capacities of a BFG holder, MSHS, wind turbine, and PV panel, aiming to achieve an economic and safe energy supply for the entire system. Multiple scenarios considering uncertain fluctuations in load demands and renewable generation are generated with the Monte Carlo method based on a typical scenario. These scenarios are then reduced to representative scenarios using the synchronous substitution and reduction method for stochastic capacity optimization to enhance the reliability of the results. The case study results demonstrate that configuring MSHS reduces the total annualized cost of the BMWS system by 2.28%. Furthermore, considering the uncertainties of the power/heating load and wind/PV generation can reduce the expected annualized total cost of the BMWS system and the corresponding standard deviation by 5.66% and 81.45%, respectively. The BMWS system can achieve 730.68 tons of equivalent CO 2 reduction in 24 h due to the successful utilization of renewable energy. This paper provides an effective approach for the decarbonization of energy generation systems in steelmaking plants.

Suggested Citation

  • Chamin Geng & Zhuoyue Shi & Xianhao Chen & Ziwen Sun & Yawei Jin & Tian Shi & Xiao Wu, 2024. "Stochastic Capacity Optimization of an Integrated BFGCC–MSHS–Wind–Solar Energy System for the Decarbonization of a Steelmaking Plant," Energies, MDPI, vol. 17(12), pages 1-19, June.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:12:p:2994-:d:1417002
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    References listed on IDEAS

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    1. Binxin Zhu & Junliang Liu & Shusheng Wang & Zhe Li, 2025. "Enhanced Models for Wind, Solar Power Generation, and Battery Energy Storage Systems Considering Power Electronic Converter Precise Efficiency Behavior," Energies, MDPI, vol. 18(6), pages 1-21, March.

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