In this section
@article{Xenos:2016:10.1115/1.4031307,
author = {Xenos, DP and Lunde, E and Thornhill, NF},
doi = {10.1115/1.4031307},
journal = {Journal of Engineering for Gas Turbines and Power-Transactions of the Asme},
title = {Optimal Operation and Maintenance of Gas Compressor Stations: An Integrated Framework Applied to a Large-Scale Industrial Case},
url = {http://dx.doi.org/10.1115/1.4031307},
volume = {138},
year = {2016}
}
TY - JOUR
AB - This paper presents a framework which integrates maintenance and optimal operation of multiple compressors. The outcome of this framework is a multiperiod plan which provides the schedule of the operation of compressors: the schedule gives the best decisions to be taken, for example, when to carry out maintenance, which compressors to use online and how much to load them. These decisions result in the minimization of the total operational costs of the compressors while at the same time the demand of the plant is met. The suggested framework is applied to an industrial gas compressor station which encompasses large multistage centrifugal compressors operating in parallel. The optimization model of the framework consists of three main parts: the models of compressor maps, the operational aspects of compressors, and a maintenance model. The results illustrate the optimal schedule for 90 days and an example of the optimal distribution of the load of the compressors for 5 days. Finally, the results show the economical benefits from the integration of maintenance and optimization.
AU - Xenos,DP
AU - Lunde,E
AU - Thornhill,NF
DO - 10.1115/1.4031307
PY - 2016///
SN - 1528-8919
TI - Optimal Operation and Maintenance of Gas Compressor Stations: An Integrated Framework Applied to a Large-Scale Industrial Case
T2 - Journal of Engineering for Gas Turbines and Power-Transactions of the Asme
UR - http://dx.doi.org/10.1115/1.4031307
UR - https://www.researchgate.net/publication/281232351_Optimal_Operation_And_Maintenance_Of_Gas_Compressor_Stations_An_Integrated_Framework_Applied_To_A_Large-Scale_Industrial_Case
VL - 138
ER -
Nina Thornhill, ABB/RAEng Professor of Process Automation
Centre for Process Systems Engineering
Department of Chemical Engineering
Imperial College London
South Kensington Campus, London SW7 2AZ
Tel: +44 (0)20 7594 6622
Email: n.thornhill@imperial.ac.uk