Strategic decision making of a biorefinery project under sustainability dimensions: A multi-objective optimization approach
Abstract
The growing of global population and its effect on food security and water supply, as well as the urgency for climate change mitigation, are issues that foster technological, social, and political innovations to increase the efficiency of the use of natural resources [1]–[3]. Among the natural resources recently investigated, biomass has interested researchers because of its widespread availability and its potential applicability as sustainable source of energy, materials and chemical products [3]. In order to integrate bio-based raw materials and new technologies, the biorefinery concept has been developed. A biorefinery is an industrial facility where biomass is transformed into a wide range of marketable products and energy [2], [4]. At the early stage of a biorefinery project, strategic decisions have to be made, including location, capacity or technology to be used, which determines its feasibility. The decision process needs to consider, not only the technological aspects themselves but also the specific conditions of the territory where the project is intended to be deployed. A recent study [5] shows that despite this problem has been treated by the MOP community, the main focus is on factors of economic profitability. However, consider the whole dimensions of sustainability, “Economic”, “Social”, “Environmental”, “Technological” and “Political” is essential in this kind of projects [6]. These dimensions determine the definition of sustainability design criteria and optimization objectives, which define a set of at least five objectives, most of the cases contradictory, to be optimized. This article develops a case study of a multiple feedstock and multiple products biorefinery to be settled up in Colombia to produce biobased polymers from Jatropha oil/Palm oil, with different technologies. The model, integrating a set of objective functions and constraints is formalized, then solved using a of the NSGA-II evolutionary algorithm. First results are discussed and implication for the project decision-making process highlighted.
Más información
Fecha de publicación: | 2017 |
Año de Inicio/Término: | October 30-31, 2017 |
Idioma: | English |
URL: | http://mopgp.org/wp-content/uploads/2017/10/MOPGP2017_final.pdf |