Optimal Multi-Objective Planning of Distributed Biorefinery Systems Involving Economic, Environmental and Social Aspects
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This work presents a multi-objective optimization model based on a mathematical programming formulation for the optimal planning of distributed biomass conversion systems. The model considers the optimal selection of feedstocks, processing technologies and products while considering a time horizon. The multi-objective optimization problem simultaneously considers the profit maximization, the environmental impact minimization, as well as the maximization of the social impact benefit through the generation of jobs in rural areas. The economic objective function takes into account the availability of bioresources, processing limits and demand of products, as well as the cost of feedstocks, products and processing routes. The environmental impact is measured through the eco-indicator-99 based on the life cycle analysis methodology. The social impact is measured through the number of jobs generated. This formulation considers the variation of parameters over time. For instance, time-based profiles for raw-material availability and product demand are considered. Although the economic and environmental objectives may contradict each other with an influence on the social impact, by means of the proposed methodology is possible to obtain a set of Pareto curves that identify the set of optimal solutions for each objective. Each Pareto curve shows the compromise between the objectives and enables a better decision about the processing of biomass. The proposed methodology is applied to a case study for planning the production of a biorefinery system in Mexico, where several scenarios that compensate the economic, social and environmental objectives are identified. 2012 Elsevier B.V.
