计及市场交易机制的含电解铝负荷的工业园区容量优化配置
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1.中国能源建设集团新疆电力设计院有限公司;2.新疆大学电气工程学院

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新疆维吾尔自治区重点研发专项项目(2022B01016);


Optimal capacity allocation of industrial parks with electrolytic aluminum load considering market trading mechanism
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    摘要:

    推动电-碳-绿证市场交易机制的发展是提升能源系统绿色、低碳转型的重要举措。现有的工业园区资源容量优化配置忽略了市场交易机制以及电解铝负荷的柔性响应的影响,难以保证园区配置方案的经济性与适用性。为此,提出了计及电-碳-绿证市场交易机制和电解铝柔性负荷的工业园区资源容量优化配置方法。首先,基于电解铝生产用能需求与调节特性,建立电解铝柔性负荷需求响应模型;其次,研究阶梯式碳-绿证交易机制,支撑含电解铝柔性负荷的工业园区节能减碳;然后,以园区年化投资-运行成本为优化目标,考虑设备投资和场地限制、设备运行等约束,建立工业园区资源容量优化配置-调度模型;最后,案例分析结果表明所提出配置方法可有效降低园区年化成本,兼顾园区新能源高效利用的同时降低碳排放。

    Abstract:

    Promoting the development of electricity-carbon-green certificate market trading mechanism is an important measure to enhance the green and low-carbon transformation of energy system. The existing optimal allocation of resource capacity in industrial parks ignores the influence of market trading mechanism and flexible response of electrolytic aluminum load, and it is difficult to ensure the economy and applicability of the park allocation scheme. Therefore, an optimal allocation method of resource capacity in industrial parks considering electricity-carbon-green certificate market trading mechanism and electrolytic aluminum flexible load is proposed. Firstly, based on the energy demand and regulation characteristics of electrolytic aluminum production, the demand response model of electrolytic aluminum flexible load is established. Secondly, it studies the stepped carbon-green certificate trading mechanism to support energy conservation and carbon reduction in industrial parks; then, taking the annual investment-operation cost of the park as the optimization goal, considering the constraints of equipment investment, site limitation and equipment operation, the optimal allocation-scheduling model of resource capacity in the industrial park is established. Finally, the case analysis results show that the proposed configuration method can effectively reduce the annual cost of the park, take into account the efficient use of new energy in the park while reducing carbon emissions.

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  • 收稿日期:2025-09-30
  • 最后修改日期:2025-11-13
  • 录用日期:2026-06-17
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