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<p>The increasing penetration of renewable energy introduces significant uncertainty to the operation of energy-intensive industries. To address this challenge, we propose a multi-timescale scheduling model for wind power integration in polysilicon industrial parks. The model consists of a day-ahead component, which minimizes operational costs by coordinating polysilicon reduction and water electrolysis hydrogen production while allocating reserve capacity. A chance-constrained programming approach is employed to determine reserve capacity, ensuring a balance between reliability and economic efficiency. The intraday component, benefiting from improved wind power forecasting accuracy, engages only the water electrolysis process to absorb excess renewable generation. By involving water electrolysis in both timescales, the model enhances operational flexibility and renewable utilization. Case studies demonstrate the effectiveness of the proposed approach, highlighting its potential to support low-carbon and cost-efficient operation in polysilicon industrial parks.</p>

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A day-ahead and intraday scheduling method for polysilicon industrial parks with wind power integration based on flexible hydrogen production coupling

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月24日

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  • Yulong Yang,
  • Chunye Qu,
  • Songnan Wang,
  • Jianwu Cai,
  • Yaodong Gong

摘要

The increasing penetration of renewable energy introduces significant uncertainty to the operation of energy-intensive industries. To address this challenge, we propose a multi-timescale scheduling model for wind power integration in polysilicon industrial parks. The model consists of a day-ahead component, which minimizes operational costs by coordinating polysilicon reduction and water electrolysis hydrogen production while allocating reserve capacity. A chance-constrained programming approach is employed to determine reserve capacity, ensuring a balance between reliability and economic efficiency. The intraday component, benefiting from improved wind power forecasting accuracy, engages only the water electrolysis process to absorb excess renewable generation. By involving water electrolysis in both timescales, the model enhances operational flexibility and renewable utilization. Case studies demonstrate the effectiveness of the proposed approach, highlighting its potential to support low-carbon and cost-efficient operation in polysilicon industrial parks.