Optimization of spatial layouts for underground facilities to achieve carbon neutrality in cities: A multi-agent system model

Abstract

Subways, underground logistics systems and underground parking, as the primary facilities types of underground, contribute significantly to the achievement of carbon-neutral cities by moving surface transportation to underground, thereby releasing surface space for the creation of more urban blue-green space for carbon sink. Therefore, in-depth studies on carbon neutrality strategies as well as reliable layout optimization solutions of these three types of underground facilities are required. This study proposes a spatial layout optimization strategy for carbon neutrality using underground hydrogen storage and geothermal energy for these three types of underground facilities employing a multi-agent system model. First, three spatial layout relationships, competition, coordination, and followership, between five underground facilities that contribute to emission reduction were investigated. Second, the implementation steps for optimizing the spatial layout of underground facilities were determined by defining the behavioral guidelines for spatial environment, underground facility, and synergistic agent. Finally, using the Tianfu New District in Chengdu City, China, as a case study, layouts of underground facilities under three different underground space development scenarios were simulated to verify the model. The findings of this study address the gap in the research on underground spatial facilities and their layout optimization in response to emission reduction. This study provided a significant reference for the study of underground space and underground resources at the planning level to aid in achieving carbon-neutral cities.

Keywords

Urban underground space (UUS)Carbon-neutral city / Multi-agent system model / Underground facility / Spatial layouts

CRediT authorship contribution statement

Lingxiang Wei: Writing - original draft, Visualization, Methodology, Investigation, Formal analysis. Dongjun Guo: Writing - review & editing, Visualization, Validation, Project administration, Funding acquisition, Conceptualization. Junyuan Ji: Visualization, Validation, Methodology, Data curation. Zhilong Chen: Writing - review & editing, Supervision, Investigation. Huapeng Hu: Visualization, Validation. Xiaoli Peng: Data curation.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Declaration of competing interest

Zhilong Chen is an editorial board member for Underground Space and was not involved in the editorial review or the decision to publish this article. All authors declare that there are no competing interests.

Acknowledgement

This work was supported by the National Natural Science Foundation of China (Grant Nos. 52378083 and 52078481) and the Natural Science Foundation of Jiangsu Province (Grant No. BK20231488). The authors thank the reviewers for their valuable comments and helpful review of this paper, which have been very helpful in improving the manuscript, and Editage (www.editage.cn) for English language editing.

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