Optimal network design of hydrogen production by integrated utility and biogas supply networks

Soonho Hwangbo, Seungchul Lee and Changkyoo Yoo

Applied Energy, 2017, vol. 208, issue C, No S0306261917314666, 195-209

Abstract: This research aims to develop a mathematical model to construct a network model for producing hydrogen by integrated utility and biogas supply networks (IUBSNs). In this model, a utility supply network exists in a huge petrochemical industry while a biogas supply network consists of a wastewater treatment plant and anaerobic digestion. Pipelines connect the utility and biogas supply networks. The steam reforming process, which is the most well-known process able to generate large amounts of hydrogen, is employed to harness hydrogen as well as to integrate the two networks. In IUBSNs, the needed steam is obtained by optimizing a utility supply network while methane-rich biogas is generated by placing anaerobic digestion tanks into a number of wastewater treatment plants allocated by region. This study uses an algorithm for solving the mixed-integer linear programming problems to minimize the total annual costs of IUBSNs and simultaneously satisfy hydrogen demand. IUBSNs can be a great alternative to a hydrogen supply network that imports and consumes fossil fuels to produce hydrogen, furthermore, it is able to positively influence environmental issues through the reduction of the amount of fossil fuel used in petrochemical industries. A case study of the Republic of Korea illustrates the feasibility of the proposed model. Three cases (base case, only optimized utility supply networks, and IUBSNs) are conducted, and an increase in hydrogen demand is applied to each case. The results demonstrate that IUBSNs construction decreases the total costs by about 13% compared to the existing situation, and as hydrogen demand increases, the gas pipeline structure in IUBSNs employs a hub city to transport biogas flexibly.

Keywords: Utility supply network; Biogas supply network; Hydrogen; Mixed-integer linear programming; Optimization (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1016/j.apenergy.2017.10.051

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