Optimization of a network of compressors in parallel: Real Time Optimization (RTO) of compressors in chemical plants - An industrial case study

Abstract

The aim of this paper is to present a methodology for optimizing the operation of compressors in parallel in process industries. Compressors in parallel can be found in many applications for example in compressor stations conveying gas through long pipelines and in chemical plants in which compressors supply raw or processed materials to downstream processes. The current work presents an optimization framework for compressor stations which describe integration of a short term and a long term optimization approach. The short-term part of the framework suggests the best distribution of the load of the compressors (where the time scale is minutes) and the long-term optimization provides the scheduling of the compressors for large time periods (where the time scale is days). The paper focuses on the short-term optimization and presents a Real Time Optimization (RTO) framework which exploits process data in steady-state operation to develop regression models of compressors. An optimization model employs the updated steady-state models to estimate the best distribution of the load of the compressors to reduce power consumption and therefore operational costs. The paper demonstrates the application of the RTO to a network of parallel industrial multi-stage centrifugal compressors, part of a chemical process in BASF SE, Germany. The results from the RTO application showed a reduction in power consumption compared to operation with equal load split strategy.