(339d) Optimization of the Operation of Integrated, Multi-Plant Systems

The use of rigorous model-based techniques for the optimizing the operation of process plants is now well established, and such techniques are implemented and deployed in both offline and online (“real-time optimization”) tools. However, increasingly, attention is shifting towards the optimization of integrated systems involving several plants sharing raw materials, intermediates and products. This is primarily driven by the fact that the decisions at the overall system level (e.g. feed allocation between plants) often have a much more significant effect on the system’s economic performance and on its ability to fulfil its requirements than decisions at the level of individual plants.

Optimization of integrated multi-plant systems is not new. In industry, it has traditionally been carried out using linear models, which greatly facilitates the solution of the underlying mathematical problem. However, this often results in solutions that actually fail to satisfy basic plant operability constraints. To some extent, this can be avoided by applying safety margins to various constraints and/or restricting the allowable range of variation of the decision variables. However, given the typical size of the money flows in these systems, the resulting sub-optimality of the solutions obtained often corresponds to significant loss of economic opportunity.

In this paper, we present a general framework for the optimization of multi-plant systems aiming to address the characteristics and requirements of real industrial applications. Aiming to exploit the increasing availability of detailed physics-based models for individual plants, the proposed framework combines these detailed models with simpler (surrogate) models derived automatically from them.