Sofía De-León Almaraz

Spatial-based Approach of the Hydrogen Supply Chain in the Midi-Pyrénées Region, France

Abstract A mathematical programming approach is developed to optimize the hydrogen supply chain in Midi-Pyrenees, the largest region of France. The aim of this study is to use a Geographical Information System (GIS) as a new tool for multi-criteria decision making after multiobjective optimization step. To have a more precise snapshot of the results obtained, the map is confronted with the one constructed with ArcGis® that contains all the geographic and demographic data of the region. This study focuses on the need to take into account such geographic data so that the various facilities can really be positioned: the results show that the production centers (small, medium and large) and the refueling stations are near as possible to the main road. This post-optimization step allows analyzing the feasible and the best solutions considering geographic criteria.

Design of a hydrogen supply chain using multiobjective optimisation

Abstract This work presents a methodology for the introduction of new criteria in a mathematical formulation dedicated to hydrogen supply chains (HSC). The optimisation approach of Almansoori and Shah [1] has been extended to develop a multiobjective design in which not only the total daily cost of the network but also its environmental and safety impacts have been considered. Results of mono and multicriteria optimisations are compared and discussed in order to highlight the main differences between both approaches.

Design and Optimization of Hydrogen Supply Chains for a Sustainable Future

Abstract The lack of existing infrastructure for hydrogen deployment is largely reported in the dedicated literature. The aim of this chapter is to present and define various pathways and technologies that can be followed to model the hydrogen supply chain (HSC) through supply chain management (SCM) concepts to efficiently integrate suppliers, manufacturers, and distributors so that hydrogen can be distributed at the right quantities, to the right locations and, at the right time, in order to optimize the main criteria (e.g., cost, risk, etc.). The modeling approaches of the HSC are described through a literature review. The pathway toward a hydrogen economy and more particularly here toward the use of hydrogen as an energy vector must encompass a broad range of items concerning the three pillars of sustainability based on economic, environmental, and social impacts. SCM models can be used to design improved business pathways which could result in reduced environmental impact while being also economically achievable. It is highlighted that more efforts can be done in fields such as demand uncertainty and social perception related to hydrogen.

Optimization of a Hydrogen Supply Chain Network Design by Multi-Objective Genetic Algorithms

Abstract Nowadays, hydrogen is considered as one of the most promising energy carriers for mobility applications. A model of the hydrogen supply chain (HSC) based on MILP formulation (Mixed Integer Linear Programming) in a multi-objective formulation implemented via the e-constraint method to generate the Pareto front was carried out in a previous work and applied to the region of Midi-Pyrenees. Yet, the size and in particular the number of binary variables often may lead to difficulties for problem solution. In this work, the potential of genetic algorithms (GA) via a variant of NSGA-II is explored to cope with the multi-objective formulation, in order to produce compromise solutions automatically. The results obtained by using GA are compared to those presented in the base model as well as the computational effort to generate the solutions. The solutions obtained by GA exhibit the same order of magnitude as those obtained with MILP in the mono-criterion problem, and some compromise solutions are produced in the multi-objective formulation.

Design of a Multi-Contaminant Water Allocation Network using Multi-Objective Optimization

Abstract The core of this study is the design of Water Allocation Networks (WAN) defined by a superstructure integrating different processes, regeneration units and contaminants. In this work, different optimization frameworks are compared to identify the main elements and criteria to be considered as well as the more robust methodology to solve problems involving multiple contaminants and several regeneration units from a multi-objective perspective. A case study previously analysed by (Feng et al., 2008) and (Boix et al., 2011) and formulated as a Nonlinear Programming (NLP) and Mixed Integer Non-Linear Programming (MINLP) problem, respectively, is treated by minimizing objective functions such as fresh water consumption, the number of network connections and the regenerated water flow rate. The comparison of the obtained results show that the use of binary variables in the MINLP approach leads to a better WAN with less connections thus eliminating low flow rates among the processes although the computation time is longer.

Design of sustainable municipal wastewater treatment plants

Abstract Nowadays, an adequate design for wastewater treatment plants (WWTP) based on optimization methods is fundamental with sustainability factors under consideration. This can be achieved by developing a systematic methodology based on models that uses as decision criteria sustainability metrics, such as costs, contaminant removal and customer value. As a preliminary analysis, two dimensions of sustainability (economic and environmental) have been studied as mono-objective functions to make evident the need for a comprehensive assessment when designing a WWTP. This was carried out considering a case study for the treatment municipal wastewater from Mexico City.