Simulation of Carbon Emission Reduction in Power Construction Projects Using System Dynamics: A Chinese Empirical Study
Autor(en): |
Lihong Li
Jing Shi Hao Liu Ruyu Zhang Chunbing Guo |
---|---|
Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Buildings, 22 November 2023, n. 12, v. 13 |
Seite(n): | 3117 |
DOI: | 10.3390/buildings13123117 |
Abstrakt: |
Power construction projects (PCPs) consume a large amount of energy and contribute significantly to carbon emissions. There is relatively little research on carbon emission reduction in PCPs, especially in predicting carbon emission reduction from a dynamic perspective. After identifying the influencing factors that promote the carbon emission reduction effect of PCPs, this study adopted a dynamic analysis method to elucidate the relationship between the variables. A quantitative carbon emission reduction system for PCPs with 51 variables was established using the system dynamics model, and the system simulation was performed using Vensim PLE software. Finally, a sensitivity analysis was conducted on four key factors: R&D investment, the prefabricated construction level, the scale of using energy-saving material, and the energy efficiency of transmission equipment. The results show that: (1) The reduction in carbon emissions from PCPs continues to increase. (2) R&D investment is the most significant factor for improving the carbon emission reduction in PCPs. (3) The value of the above four influencing factors should be increased within a reasonable range so that the four factors can work better to promote the carbon emission reduction effect of PCPs. This paper creatively proposes a dynamic prediction model for carbon emission reduction in the PCP, and the research results provide the scientific basis for government supervision and enterprise decision-making. |
Copyright: | © 2023 by the authors; licensee MDPI, Basel, Switzerland. |
Lizenz: | Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden. |
2.23 MB
- Über diese
Datenseite - Reference-ID
10753906 - Veröffentlicht am:
14.01.2024 - Geändert am:
07.02.2024