赵书琪,徐建军,腾新亮,李一凡,彭程,闫丽梅
ZHAO Shuqi,XU Jianjun,TENG Xinliang,LI Yifan,PENG Cheng,YAN Limei

• 1:东北石油大学提高油气采收率教育部重点实验室
• 2:东北石油大学电气信息工程学院
• 3:中国石油集团电能有限公司广西新能源项目经理部

摘要(Abstract)：

双碳目标背景下，新型电力系统的结构愈发复杂，通过协调系统中的源、荷、储得到经济低碳的配电网运行方案，是当前的重点研究内容。为此，提出一种基于碳排放流理论的配电网低碳经济调度模型。首先，建立基于二阶锥潮流模型的配电网经济调度模型；其次，根据经济调度结果，计算各节点碳势，并通过迭代法解决碳势计算过程中储能设备初始碳存储量未知的问题；然后，以碳排放量和新能源舍弃量最低为目标，构建低碳需求响应模型；最后，以IEEE 33节点配电网为例进行仿真实验，基于IEEE123节点对模型的计算效率进行分析，并给出其他三种模型进行对比。实验结果表明，提出的低碳调度模型可在保证经济性的情况下，有效降低碳排放量，缩短计算时间，具有很好的应用前景。
In the context of dual carbon goals, the structure of the new-type power systems is becoming increasingly complex. Coordinating sources, loads, and energy storage within the systems to achieve economically efficient and low-carbon operation of distribution networks is a key area of current research. To address this, a low-carbon and economically efficient dispatch model for distribution networks based on carbon emission flow theory is proposed.First, an economically efficient dispatch model for distribution networks is established using a second-order cone flow model. Next, carbon potentials at each node are calculated based on the dispatch results, and an iterative method is employed to resolve the issue of unknown initial carbon storage levels in energy storage devices during the carbon potential calculation. Subsequently, a low-carbon demand response model is constructed with the goals of minimizing carbon emissions and the amount of curtailed renewable energy. Finally, simulation experiments are conducted using the IEEE 33-bus distribution network as an example, and the computational efficiency of the model is analyzed based on the IEEE 123-bus network. Comparisons are made with three other models. Experimental results indicate that the proposed dispatch model effectively reduces carbon emissions while maintaining economic efficiency and shortening calculation time, demonstrating promising application potential.

关键词(KeyWords)： 低碳经济调度;碳排放流理论;需求响应;主动配电网
low-carbon and economically efficient dispatch;carbon emission flow theory;demand response;active distribution network

Abstract:

Keywords:

基金项目(Foundation): 黑龙江省自然科学基金资助项目（LH2019E016）

作者(Author): 赵书琪,徐建军,腾新亮,李一凡,彭程,闫丽梅
ZHAO Shuqi,XU Jianjun,TENG Xinliang,LI Yifan,PENG Cheng,YAN Limei

DOI: 10.19585/j.zjdl.202412013

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