
1. 华南理工大学 电力学院,广东,广州,510641
2. 南方电网能源发展研究院 配电网规划研究部,广东,广州,510530
3. 澳门大学 智慧城市物联网全国重点实验室,电机及电脑工程系,澳门,999078
Online First:22 June 2026,
Published:2026
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翁亮涛, 肖天颖, 郑伟业. 区域供热网络等效储能模型及其在非迭代电热联合调度中的应用[J]. 中国电力, 2026, 59(6): 145-153.
WENG Liangtao, XIAO Tianying, ZHENG Weiye. Equivalent energy storage model for district heating network and its application in non-iterative combined electricity-heat scheduling[J]. 2026, 59(6): 145-153.
翁亮涛, 肖天颖, 郑伟业. 区域供热网络等效储能模型及其在非迭代电热联合调度中的应用[J]. 中国电力, 2026, 59(6): 145-153. DOI: 10.11930/j.issn.1004-9649.202509039.
WENG Liangtao, XIAO Tianying, ZHENG Weiye. Equivalent energy storage model for district heating network and its application in non-iterative combined electricity-heat scheduling[J]. 2026, 59(6): 145-153. DOI: 10.11930/j.issn.1004-9649.202509039.
区域供热网络因其热惯性而具有巨大的储能潜力,能够为电力系统提供灵活性。然而,热网的复杂能量传输特性和数据隐私问题使得难以评估其储能能力。为此,提出了一种计及热网动态特性的近似模型来聚合热网的储能能力。首先,将热网的灵活性建模为一个物理意义明确的等效储能模型以量化管道热储能能力;然后,采用基本多面体平移缩放方法计算热网的等效储能模型参数;最后,将热网的灵活性聚合模型应用于电热综合能源系统的协同优化中,并进行仿真验证。仿真结果表明,所提聚合模型在避免集中式方法中详细热网模型的同时,能够以非迭代的方式求解电热联合调度问题,且结果具有较高的精度。
District heating networks exhibit considerable energy storage potential due to their thermal inertia
enabling sufficient operational flexibility for power systems. However
the complex energy transfer characteristics and data privacy concerns of heating networks pose great challenges to the accurate evaluation of their storage capability. To address this issue
an approximate model considering dynamic properties of heating networks is proposed to aggregate the storage capacity of heating networks. First
the flexibility of the heating network is modeled as a physically meaningful equivalent energy storage model to quantify the thermal storage capacity of pipelines. Building upon this
the basic polyhedron translation and scaling method is employed to determine the parameters of the heating network equivalent energy storage model. Furthermore
the proposed flexibility aggregation model is applied to the coordinated optimization of integrated electricity-thermal energy systems
and numerical simulations are conducted for validation. Simulation results demonstrate that the proposed aggregation model can solve the combined power-heat dispatch problem non-iteratively while avoiding the detailed heating network modeling required by conventional centralized approaches. Meanwhile
the optimized results can maintain a high level of computational accuracy.
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