A systematic framework for CAFD and resources allocation optimisation using MINLP in vegetable oil processing

Although being a mature and well established industry segment, over the last few decades the vegetable oil industry has been facing many important new challenges due to emerging new products (such as biodiesel and nutraceuticals compounds), as well as new trends and regulations with regards to sustainability, environment and health. Most of the time, the industry reacted to these challenges taking decisions based on previous experiences or heuristic, or with the help of tools which arguably were not fit to manage the complexity of the entire value chain, and therefore often led to suboptimal outcomes. In this paper, a systematic framework for Computer-Aided Flowsheet Syntesis and Design (CAFD) and resources allocation for the vegetable oil sector is presented. In the framework a Mixed Integer Non Linear Programming (MINLP) problem is formulated and solved for a soybean processing case study, to determine the optimal processing network for vegetable oil extraction and refining (including biodiesel production and various options for byproducts valorization), as well as the optimal material flows to each processing step. In order to optimize the resources needed to solve such a large and complex problem, an efficient and systematic solution strategy based on the use of shortcut calculations to eliminate infeasible and redundant options to reduce the search space for the rigorous optimization problem is adopted. One of the main advantages of the use of this framework is its ability to generate different scenarios by changing the input data, without having to modify the model structure. Also, the framework can be adapted to different purposes, from retrofit of existing operations to new plant design, by changing variable specifications.