Optimization of a network of compressors in parallel: Real Time Optimization (RTO) of compressors in chemical plants - An industrial case study
File(s)
Author(s)
Type
Journal Article
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.
Date Issued
2015-04-15
Date Acceptance
2015-01-04
Citation
Applied Energy, 2015, 144 (1), pp.51-63
ISSN
0306-2619
Publisher
Elsevier
Start Page
51
End Page
63
Journal / Book Title
Applied Energy
Volume
144
Issue
1
Copyright Statement
© 2014 Elsevier B.V. All rights reserved. NOTICE: this is the author's version of a work that was accepted for publication in Applied Energy. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in APPLIED ENERGY, Vol.: 144 (2015) DOI: 10.1016/j.apenergy.2015.01.010
Sponsor
Commission of the European Communities
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000353008300005&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
PITN-GA-2010-264940
Subjects
Science & Technology
Technology
Energy & Fuels
Engineering, Chemical
Engineering
Real time optimization
Industrial compressors
Optimal load sharing
Mathematical programming
Regression models
Energy savings
ONLINE OPTIMIZATION
DESIGN
DOMAIN
MODEL
Publication Status
Published
Date Publish Online
2015-02-06