Optimal design of sustainable hydrogen networks

• Published in: International journal of hydrogen energy Vol. 38; no. 7; pp. 2937 - 2950
• Main Authors: Zhou, Li, Liao, Zuwei, Wang, Jingdai, Jiang, Binbo, Yang, Yongrong, Hui, David
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 07.03.2013; Elsevier
• Subjects: Alternative fuels. Production and utilization; Applied sciences; Economic; Energy; Exact sciences and technology; Fuels; Greenhouse gas emission; Hydrogen; Mathematical modeling; Multi-objective optimization; Sustainable hydrogen network; Greenhouse gas emission; HNI; Economic; Sustainable hydrogen network; SHNI; GHG; MINLP; Mathematical modeling; Multi-objective optimization; PSA; Hydrogen; Pollutant emission; Modeling; Optimization; Optimal design
• ISSN: 0360-3199; 1879-3487
• DOI: 10.1016/j.ijhydene.2012.12.084

Hydrogen is widely used in modern oil refineries to remove the sulfur, nitrogen and aromatic contents of fuels. The existence of such contents would aggravate the greenhouse gas (GHG) emission of petrol fuels. The ultimate goal of massive hydrogen consumption in refineries is to cut down the GHG emission. However, current researches on hydrogen networks are focusing on reducing the cost of hydrogen consumption. The environmental impact of hydrogen consumption, especially the GHG emission, has not been considered yet. If the hydrogen supply network itself discharges too much CO2, then the significance of the hydrogen consumption will be discounted considerably. It is of great importance to design a sustainable hydrogen network. This paper presents a systematic mathematical modeling methodology for the optimal synthesis of sustainable refinery hydrogen networks. The proposed mixed integer nonlinear programming (MINLP) model accounts for both the economic and the environmental aspect of the hydrogen network. Total annual cost (TAC) is employed to evaluate the economic efficiency of the network, while the environmental performance is assessed by the total CO2 emission of the network. Two types of fresh fuels are investigated in the case studies. A multi-objective optimization is carried out via the Pareto front generation, which is obtained by an adaptive weighted-sum method. The economic–environmental Pareto front will allow for determining the most promising options for the reuse, purification and combustion of hydrogen streams. The numerical example has shown the proposed approach to be efficient and powerful. ► Purifiers are considered in the multi-contaminant hydrogen network. ► Both the environmental impact and economical performance are optimized. ► Two types of fresh fuels are considered in the case studies. ► A sustainable hydrogen network is generated.