Multi-Objective Optimal Design of a Hydrogen Supply Chain Powered with Agro-Industrial Wastes from the Sugarcane Industry: A Mexican Case Study

Luis Miguel Reyes-Barquet, José Octavio Rico-Contreras, Catherine Azzaro-Pantel, Constantino Gerardo Moras-Sánchez, Magno Angel González-Huerta, Daniel Villanueva-Vásquez and Alberto Alfonso Aguilar-Lasserre
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Luis Miguel Reyes-Barquet: Graduate Studies and Research Division, Tecnológico Nacional de México/Instituto Tecnológico de Orizaba, Calle Oriente 9 Colonia Emiliano Zapata, Orizaba 94320, Mexico
José Octavio Rico-Contreras: Grupo Porres Corporativo, Km 355 Carretera Federal Fortín de las Flores, Cordoba 94540, Mexico
Catherine Azzaro-Pantel: Laboratoire de Génie Chimique, Université de Toulouse, U.M.R. 5503 CNRS/INP/UPS, 4 allée Emile Monso, CEDEX 4, 31432 Toulouse, France
Constantino Gerardo Moras-Sánchez: Graduate Studies and Research Division, Tecnológico Nacional de México/Instituto Tecnológico de Orizaba, Calle Oriente 9 Colonia Emiliano Zapata, Orizaba 94320, Mexico
Magno Angel González-Huerta: Graduate Studies and Research Division, Tecnológico Nacional de México/Instituto Tecnológico de Orizaba, Calle Oriente 9 Colonia Emiliano Zapata, Orizaba 94320, Mexico
Daniel Villanueva-Vásquez: Departamento de Investigación y Posgrado, Tecnológico Nacional de México/Instituto Tecnológico Superior de Misántla, Km 1.8 Carretera a Lomas de Cojolite, Misantla 93821, Mexico
Alberto Alfonso Aguilar-Lasserre: Graduate Studies and Research Division, Tecnológico Nacional de México/Instituto Tecnológico de Orizaba, Calle Oriente 9 Colonia Emiliano Zapata, Orizaba 94320, Mexico

Mathematics, 2022, vol. 10, issue 3, 1-42

Abstract: This paper presents an optimization modeling approach to support strategic planning for designing hydrogen supply chain (HSC) networks. The energy source for hydrogen production is proposed to be electricity generated at Mexican sugar factories. This study considers the utilization of existing infrastructure in strategic areas of the country, which brings several advantages in terms of possible solutions. This study aims to evaluate the economic and environmental implications of using biomass wastes for energy generation, and its integration to the national energy grid, where the problem is addressed as a mixed-integer linear program (MILP), adopting maximization of annual profit, and minimization of greenhouse gas emissions as optimization criteria. Input data is provided by sugar companies and the national transport and energy information platform, and were represented by probability distributions to consider variability in key parameters. Independent solutions show similarities in terms of resource utilization, while also significant differences regarding economic and environmental indicators. Multi-objective optimization was performed by a genetic algorithm (GA). The optimal HSC network configuration is selected using a multi-criteria decision technique, i.e., TOPSIS. An uncertainty analysis is performed, and main economic indicators are estimated by investment assessment. Main results show the trade-off interactions between the HSC elements and optimization criteria. The average internal rate of return (IRR) is estimated to be 21.5% and average payback period is 5.02 years.

Keywords: sugarcane bagasse; hydrogen energy; electrolysis; MILP; multi-criteria optimization; genetic algorithm; uncertainty; Monte Carlo simulation; TOPSIS (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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