Design of a sustainable supply chain network of biomass renewable energy in the case of disruption

被引:0
|
作者
Aslani, Leila [1 ]
Hasan-Zadeh, Atefeh [1 ]
Kazemzadeh, Yousef [2 ]
Sheikh-Azadi, Amir-Hosein [1 ]
机构
[1] Univ Tehran, Coll Engn, Fouman Fac Engn, POB 4358139115, Fouman, Iran
[2] Persian Gulf Univ, Fac Petr Gas & Petrochem Engn, Dept Petr Engn, Bushehr, Iran
来源
SCIENTIFIC REPORTS | 2024年 / 14卷 / 01期
关键词
Biomass supply chain; Genetic algorithm; Simulated annealing algorithm; Stability; Disruption; OPTIMIZATION MODEL; MANAGEMENT; CHALLENGES; BIOENERGY; GAS;
D O I
10.1038/s41598-024-64341-9
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Non-renewable energy sources, including fossil fuels, are a type of energy whose consumption rate far exceeds its natural production rate. Therefore, non-renewable resources will be exhausted if alternative energy is not fully developed, leading to an energy crisis in the near future. In this paper, a mathematical model has been proposed for the design of the biomass supply chain of field residues that includes several fields where residue is transferred to hubs after collecting the residue in the hub, the residue is transferred to reactors. In reactors, the residue is converted into gas, which is transferred to condenser and transformers, converted into electricity and sent to demand points through the network. In this paper, the criteria of stability and disturbance were considered, which have been less discussed in related research, and the purpose of the proposed model was to maximize the profit from the sale of energy, including the selling price minus the costs. Genetic algorithm (GA) and simulated annealing (SA) algorithm have been used to solve the model. Then, to prove the complexity of the problem, different and random examples have been presented in different dimensions of the problem. Also, the efficiency of the algorithm in small and large dimensions was proved by comparing GA and SA due to the low deviation of the solutions and the methods used have provided acceptable results suitable for all decision-makers. Also, the effectiveness of the algorithm in small and large dimensions is proven by comparing the genetic algorithm and simulated annealing, and the genetic algorithm's values are better, considering the deviation of 2.9%.and have provided solution methods suitable for all decision makers.
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页数:18
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