电-碳耦合机制下的区域能源系统双层低碳优化
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作者单位:

1. 国网能源研究院有限公司,北京 102209 ;2. 国网四川省电力公司 电力科学研究院,成都 610095

作者简介:

孙广增(1994),男,内蒙古自治区赤峰人,博士,高级工程师,主要从事能源电力规划、电力系统运行分析、能源交通融合等领域研究工作。

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中图分类号:

TM721

基金项目:

国家电网有限公司总部科技项目(1400-2024 26279A-1-1-ZN)


Bi-level low-carbon optimization of regional energy systems under power-carbon coupling mechanisms
Author:
Affiliation:

1. State Grid Energy Research Institute Co., Ltd., Beijing 102209 , China ;2. Electric Power Research Institute, State Grid Sichuan Electric Power Company, Chengdu 610095 , China

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    摘要:

    在“双碳”目标深入实施的背景下,园区综合能源系统日益成为能源管理与资源调度的双重主体。然而,现有研究多孤立考虑需求响应或优化调度,缺乏源荷协同优化措施。因此,提出一种考虑电-碳需求响应的综合能源系统双层低碳优化调度模型。首先,构建了面向园区运营商的需求响应与优化调度联合框架;其次,提出基于动态碳排放因子的多能碳排放计量方法,建立了考虑“电视角”与“碳视角”的综合需求响应模型;最后,建立了园区需求响应与优化调度的双层优化模型,通过负荷碳排放因子迭代更新,实现模型优化求解。算例分析表明考虑电碳需求响应后,较未考虑需求响应下运营商总成本降低4.15%,碳排放减少14.3%。

    Abstract:

    Under the deep implementation of the “Dual-Carbon” strategy, integrated energy systems (IESs) in industrial parks are increasingly taking on the dual roles of energy management and resource scheduling. However, demand response and optimal dispatch are often investigated separately, and coordinated supply-demand low-carbon optimization remains insufficient. To address this gap, a bi-level low-carbon optimization model for industrial-park IESs considering electricity-carbon demand response is proposed. A unified framework that couples demand response and optimal dispatch from the operator perspective is constructed. A dynamic multi-energy carbon-emission factor calculation method is developed, and a comprehensive demand response model integrating both electricity and carbon perspectives is established. A bi-level optimization model is further formulated, where carbon-emission factors are iteratively updated based on load adjustments to achieve solution convergence. Case studies show that, compared with the electricity-only demand response case, the total cost for operators is reduced by 4.15%, and carbon emissions are reduced by 14.3%.

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引用本文

孙广增,元博,鲁刚,张涵,龚一莼.电-碳耦合机制下的区域能源系统双层低碳优化[J].电力需求侧管理,2026,28(2):86-92

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  • 收稿日期:2026-01-13
  • 最后修改日期:2026-02-01
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  • 在线发布日期: 2026-07-20
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