Iterative real-time optimization of a membrane pilot plant

Abstract

In this paper, we describe the implementation and experimental validation of iterative real-time optimization (RTO) at a continuously operated membrane separation pilot plant. The objective is to achieve an economically optimal operation using the transmembrane pressure and the feed flow rate as adjustable operational parameters (set-points for the lower-level plant controllers). In spite of the popularity of RTO based on rigorous nonlinear plant models in the research literature, its practical use so far remains limited to large scale plants in the petrochemical industries. The main issue behind the limited application of RTO schemes is the necessary effort to derive and maintain sufficiently accurate models of the plants. In case of a significant plant-model mismatch, the results are not reliable, the optimal performance is not reached and even systematic violations of constraints may occur. The applicability of RTO could be extended significantly if simple process models sufficed for its successful application. Then an adaptation of the model or of the optimization problem to the real behavior of the plant is necessary to achieve an optimal operation. For this example, we tackle this issue by applying an iterative scheme called modifier-adaptation with quadratic approximation in combination with model adaptation to ensure the convergence of the plant to the true process optimum despite the fact that the model has deficiencies. The experimental results show that, in spite of a considerable plant-model mismatch, the presented RTO scheme is capable of boosting the process economics.