Paper
16 January 2025 Research on the risk control of straw power generation supply chain based on system dynamics
Qingqing Qu, Guangyin Xu, Zhenfeng Wang, Heng Wang, Zhanwu Wang, Jin Li, Xiaohan Gao, Jingbo Fu
Author Affiliations +
Proceedings Volume 13447, International Conference on Mechatronics and Intelligent Control (ICMIC 2024); 1344713 (2025) https://doi.org/10.1117/12.3050269
Event: International Conference on Mechatronics and Intelligent Control (ICMIC 2024), 2024, Wuhan, China
Abstract
Straw power generation can reduce pollutant emissions and alleviate the energy crisis. However, the development of straw power generation supply chain is affected by various risk factors. Therefore, this study clarified the internal structure and feedback mechanisms of the risk factor system, and constructed the system dynamics model of the straw power generation supply chain to explore the impact of risk factors on the supply chain in terms of cost. Subsequently, simulations were carried out using the Vensim PLE software. The results indicate that environmental risk has the greatest impact on the total cost of straw power generation supply chain, followed by market risk and information risk, with technical risk having the least impact. Finally, Risk control strategies were proposed for the most influential risks, and the system dynamics simulation was carried out. The results show that the effect of information risk control strategies are the most effective, followed by market risk and environmental risk. This study provides a theoretical foundation for the risk control in straw power generation supply chain and contributes to the sustainable development of the straw power generation industry.
(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Qingqing Qu, Guangyin Xu, Zhenfeng Wang, Heng Wang, Zhanwu Wang, Jin Li, Xiaohan Gao, and Jingbo Fu "Research on the risk control of straw power generation supply chain based on system dynamics", Proc. SPIE 13447, International Conference on Mechatronics and Intelligent Control (ICMIC 2024), 1344713 (16 January 2025); https://doi.org/10.1117/12.3050269
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KEYWORDS
Control systems

Transportation

Systems modeling

Data storage

Simulations

Environmental management

Environmental sensing

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