مهندسی مکانیک شریف (May 2020)
ANALYSIS AND OPTIMIZATION OF THE NGL PLANT USING THE EXTENDED BRIDGE - EXERGY METHOD AND DIFFERENTIAL EVOLUTION ALGORITHM
Abstract
The purpose of this manyscript includes providing new analysis and optimization method in process systems which is achieved due to the strengths of the simultaneous analytical methods of energy-exergy for thermal and chemical systems. In this treatise, it has been tried to with doing a comprehensive research effort, a new method is proposed to target energy-exergy process systems with help of other techniques in order to be useful in analyzing and optimizing process systems. In addition, exergy, exergyeconomic and pinch methods have been introduced according to the need and importance of relevant analyzes. In the following, the developed method in the synchronous combination of Pinch-Exergy called Bridge-Exergy is presented at two different levels for analyzing the energy and exergy process systems simultaneously. The output of this developed bridge-exergy method is a new and correlated equation for the simultaneous analysis of energy and exergy, which it leads to creation of an Exergy Transmission Curve (ETC) for thermal equipment and an energy exergy destruction curve (EDL) and an energy --- exergy cost destruction curve (ECDL) for equipment including pressure and composition change. Hereafter using this method of combining and analyzing the equipment of the process system, by using the artificial intelligence method called differential evolution algorithm, the optimization and integration of the whole process system are done simultaneously. Finally, based on the developed energy-exergy analysis method, a new algorithm is introduced and evaluated for the design of optimal process systems. As a field study for investigating the bridge-exergy combination method and optimization algorithm, NGL production process has been briefly investigated and thoroughly analyzed and optimized. In the process of natural gas separation, using the bridge-exergy combination method and artificial intelligence method, the differential evolution algorithm, the operating cost is reduced about 44 \% and the annual profit is increased to about 814400 (\$/year).
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