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Real-time optimization of load sharing for gas compressors in the presence of uncertainty
Publikationstyp
Journal Article
Date Issued
2020-08-15
Sprache
English
Author(s)
Milosavljevic, Predrag
Cortinovis, Andrea
Mercangöz, Mehmet
Journal
Volume
272
Article Number
114883
Citation
Applied Energy 272: 114883 (2020-08-15)
Publisher DOI
Scopus ID
Publisher
Elsevier
This paper investigates the problem of load-sharing optimization of gas compressors in the presence of uncertainty. The objective is to operate a set of compressor units in an energy-efficient way, while at the same time meeting a varying load demand. The main challenge is the fact that the available models, and in particular the compressor efficiency maps, carry a significant amount of uncertainty. For this task, real-time optimization (RTO) techniques that rely on plant measurements and correct the model are available in the literature. This paper is tailored to the application of RTO to the compressor load-sharing optimization problem. An adaptive optimization approach that guarantees optimal plant operation upon convergence is used. To this end, we use appropriate measurements to estimate plant gradients and correct the model in such a way that it exhibits the same optimality conditions as the plant. This way, the challenge is shifted from having an accurate model to being able to estimate experimental gradients accurately. We show how the specific problem structure can be exploited for the purpose of efficient estimation of plant gradients. We consider both parallel and serial compressor configurations as well as operation close to surge constraints. The simulation of an industrial case study demonstrates the efficiency of the proposed approach.
Subjects
Adaptive optimization
Gas compressors
Interconnected systems
Optimal load sharing
Real-time optimization
DDC Class
530: Physics