Production and Logistics Planning Method of New Energy Industry Supply Chain Under the Background of Low Carbon

被引:1
作者
Bai, Binli [1 ]
机构
[1] Anhui Vocational College of Defense Technology, Anhui, Lu'An
来源
Renewable Energy and Power Quality Journal | 2024年 / 22卷 / 01期
关键词
Low-carbon Policy; New Energy Industry; Planning Method; Production Logistics; Supply Chain;
D O I
10.52152/3954
中图分类号
学科分类号
摘要
In the context of low carbon, new energy, as an emerging financing method in the industrial supply chain, has obvious advantages in alleviating production costs and changing logistics methods. However, the limited energy storage of new energy and the path distance being smaller than that of traditional energy transportation modes bring specific challenges to supply chain logistics planning. With the help of the logistic model, this paper analyzes the path of the industrial supply chain logically, finds out the influencing factors that affect the logistics planning of the supply chain, and calculates it. Among them, the intervention factors in the path, such as traffic congestion, traffic light, and path angle, are analyzed and judged, redundant interference factors are eliminated, and the adjustment coefficient of logistics planning is increased to realize the effective planning of production logistics and expand the development of new energy industry, and the research results show that with the help of logical analysis method, the rational planning of production logistics can be shortened by about 20%, the transportation efficiency can be improved by about 15%, the traffic congestion avoidance rate can be reduced by 10%, and the transportation cost can be saved by about 104,200 yuan. Therefore, through logistics planning, the new energy industry supply chain can conduct a reasonable path analysis, meet the policy standards of green production and transportation, and expand the development scope of the new energy industry. © 2024, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.
引用
收藏
页码:102 / 110
页数:8
相关论文
共 39 条
[21]   Definition method for carbon footprint of iron and steel energy supply chain based on relational dispersed degree [J].
Meng, Hua ;
Wang, Weixin .
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2020, 38 (06) :7407-7416
[22]   Supply chain low-carbon R&D strategy considering carbon tax under the sustainable development goals [J].
Sun, Jiasen ;
Yuan, Pengpeng ;
Li, Guo .
ANNALS OF OPERATIONS RESEARCH, 2025,
[23]   Low-Carbon Collaboration in the Supply Chain under Digital Transformation: An Evolutionary Game-Theoretic Analysis [J].
Li, Gang ;
Yu, Hu ;
Lu, Mengyu .
PROCESSES, 2022, 10 (10)
[24]   Optimal Policy for Manufacturer-Retailer Having Two Warehouse Storage Supply Chain Models with Reverse Logistics under Carbon Tax Policy [J].
Singh, S. R. ;
Gaur, Anjali ;
Singh, Dipti ;
Padiyar, S. V. Singh .
PROCESS INTEGRATION AND OPTIMIZATION FOR SUSTAINABILITY, 2025, 9 (03) :939-953
[25]   The abatement contract for low-carbon demand in supply chain with single and multiple abatement mechanism under asymmetric information [J].
Li, Jian ;
Lai, Kin Keung .
ANNALS OF OPERATIONS RESEARCH, 2023, 324 (1-2) :437-459
[26]   The abatement contract for low-carbon demand in supply chain with single and multiple abatement mechanism under asymmetric information [J].
Jian Li ;
Kin Keung Lai .
Annals of Operations Research, 2023, 324 :437-459
[27]   Maximizing efficiency in low-carbon sustainable supply chain under yield uncertainty and risk-averse flexibility [J].
Barman, Abhijit ;
Sarkar, Pinak ;
Kalisz-Szwedzka, Katarzyna ;
Weber, Gerhard-Wilhelm .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2025,
[28]   Selection of Symmetrical and Asymmetrical Supply Chain Channels for New Energy Vehicles Under Multi-Factor Influences [J].
Tong, Yongjia ;
Dong, Jingfeng .
SYMMETRY-BASEL, 2025, 17 (05)
[29]   A Sustainable Supply Chain Model with Low Carbon Emissions for Deteriorating Imperfect-Quality Items under Learning Fuzzy Theory [J].
Alsaedi, Basim S. O. ;
Ahelali, Marwan H. .
MATHEMATICS, 2024, 12 (08)
[30]   A Unified Optimization Model with Proportional Fairness and Robustness of Fuzzy Multi-Objective Aggregate Production Planning in Supply Chain under Uncertain Environments [J].
Sutthibutr, Noppasorn ;
Chiadamrong, Navee ;
Hiraishi, Kunihiko ;
Thajchayapong, Suttipong .
ENGINEERING JOURNAL-THAILAND, 2024, 28 (05) :25-52