The design of multiple-feedstock multiple-product processing networks involves the consideration of many different conversion technologies that link feedstocks to products through several possible intermediates. Traditional approaches aimed to find the best set of products and the most convenient processing pathways, involve the development of a conversion superstructure and the formulation and solution of a mathematical optimization problem. In recent years, such an approach has been successfully applied to the design of biorefinery networks, albeit those in which the set of target products was small and a priori known, and the technologies were well defined. However, when the set of possible products is very large or the technologies for conversion of different intermediates are still under development, the proposal and solution of a single, master, superstructure results impractical.
Motivated by the need of a more flexible approach, in our previous work we proposed a novel strategy for the design of optimal biorefinery networks. Drawing a parallel with a petrochemical network, we divided the biorefinery in (i) one supplier that produces multiple intermediates, and (ii) several consumers that upgrade these intermediates to different products. The key difference with the traditional approach is that, instead of considering a single actor process, the supplier and the consumers are considered to act independently of each other and thus seek the maximization of their own profit. Under this assumption a multiobjective optimization problem (MOP) was formulated to find the optimal set of design variables, flowrates and transfer prices for the intermediates. Using a two-level Lagrangian approach we proved that the MOP could be simplified into a separable optimization problem, to find the solution that, while attaining the same profit level as the single actor network, also maximized the profits of the individual actors. Further, we also showed that this solution was obtained when the price at which the intermediates were transferred coincides with the optimal value of the Lagrange multipliers.
In this presentation, we extend the previous framework to generic processing networks that may also be modeled by the suppliers-intermediates-consumers scheme discussed before. We begin by considering the presence of several suppliers that produce competing intermediates, and study how the earlier analysis change when a consumer can use the same processing steps to upgrade the competing intermediates and when additional processing steps are required. As a particular case, we consider the market as one of the competing suppliers. Then, we generalize the term intermediate to include the exchange of energy, and in particular, we analyze energy integration between the different consumers. Finally, the developed framework is exemplified through a case study that considers generic equations to estimate capital and operational costs for the different actors.
This work was funded by the Cooperative Agreement between the Masdar Institute of Science and Technology (Masdar Institute), Abu Dhabi, UAE and the Massachusetts Institute of Technology (MIT), Cambridge, MA, USA - Reference 02/MI/MI/CP/11/07633/GEN/G/00 for work under the Second Five Year Agreement.