CCUS Pipeline Network Layout Optimization Method Based on DBSCAN Clustering

doi:10.12388/j.issn.1673-2677.2025.03.006

Abstract

Abstract:

To mitigate climate change by reducing CO₂ emission，carbon capture，utilization，and storage （CCUS） technologies have garnered significant attention. However，the required large scale investment and inflexibility of CCUS projects have greatly hindered their widespread applications. In this context，systematic source-sink matching has emerged as a key research focus，as scientific and efficient matching can optimize pipeline network design and reduce the overall costs of CCUS implementation. To this end，this study proposes a CCUS pipeline network layout optimization method using Density-Based Spatial Clustering of Applications with Noise （DBSCAN），offering a solution for CCUS pipeline network design. Firstly，the DBSCAN clustering is employed to cluster emission sources and storage sinks. Subsequently，a CCUS source-sink matching model is developed based on the minimum spanning tree method after comprehensively considering source-sink characteristics and cost components across operational phases to generate theoretical CCUS matching schemes. Finally，to address pipeline redundancy caused by multi-sources to one-sink configurations，an improved saving algorithm is applied to optimize the CCUS source-sink matching scheme. A hypothetical planning region is presented for testing of the proposed method，which demonstrates that the model does not only reduce deployment costs but also significantly shortens transportation distances. Compared with traditional methods，the total deployment costs decrease from 130 billion CNY to 98 billion CNY，by a reduction of approximately 24.6%，while the transportation distance is reduced from 4 075 km to 1 008 km，marking a decrease of 75.3%. These findings validate the adaptability and economic efficiency of the proposed method in complex CCUS scenarios，and the proposed method provides a feasible optimization pathway and theoretical foundation for CCUS system planning.

Key words:

source-sink matching, CCUS, minimum spanning tree method, improved saving algorithm, DBSCAN clustering

摘要：

为减少CO₂排放，减缓气候变化，碳捕集、利用和封存（CCUS）技术受到了广泛关注。由于项目投资较大且不易变更，CCUS技术的推广和应用受到了极大限制。目前系统化的源汇匹配已成为研究重点，科学、有效的源汇匹配可优化管网设计，降低CCUS全流程成本。提出了一种基于密度的具有噪声的聚类算法（DBSCAN）优化CCUS管网布局，为CCUS管网设计提供解决方案。首先应用DBSCAN算法对源和汇进行聚类处理；然后在充分考虑源汇性质、各环节成本等因素基础上，基于最小支撑树法构建CCUS源汇匹配模型，得到CCUS源汇匹配理论方案；最后针对多源共汇导致的管网冗余问题，应用改进的节约里程法优化CCUS源汇匹配方案。以假定规划区为例开展研究，结果表明所提模型不仅能够降低CCUS部署成本，还能大幅缩短运输距离。相较于传统方案，部署总成本由1.3×10⁷万元降至9.8×10⁶万元，降幅约为24.6%；运输距离由4 075 km减少至1 008 km，降幅达75.3%。研究验证了所提方法在复杂CCUS场景中的适应性与经济性，为CCUS系统规划提供了可行的优化路径和理论参考。

关键词:

源汇匹配, CCUS, 最小支撑树法, 改进的节约里程法, DBSCAN聚类

CLC Number:

X701

ZHAO Dongya, HUANG Qizhan, XING Yupeng, ZHANG Ni, YU Hui, XU Baoshen. CCUS Pipeline Network Layout Optimization Method Based on DBSCAN Clustering[J]. Xinjiang Oil & Gas, 2025, 21(3): 50-60.

赵东亚, 黄启展, 邢玉鹏, 章旎, 于徽, 许保珅. 基于DBSCAN聚类的CCUS管网布局优化方法[J]. 新疆石油天然气, 2025, 21(3): 50-60.

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