Automated Pinch-Exergy Analysis for Industrial Processes: ΔTmin Effect on Energy and Exergy Targets

Document Type : SEMIT 2022

Authors

1 Applied Mathematics and Computer Science Decision Laboratory,National Graduate Engineering School Of Mines - Rabat- Morocco

2 Information Technology and communications Laboratory, International University of Rabat, Rabat.

3 Applied Mathematics and Computer Science Decision Laboratory, National Graduate Engineering School Of Mines - Rabat- Morocco

Abstract

Energy efficiency and process integration play a vital role in minimizing fossil fuel consumption and electricity demand within industrial processes. Therefore, experts have prioritized research on enhancing and promoting the thermal energy efficiency of this sector, with a specific emphasis on energy recovery and sustainability goals. Pinch analysis (PA) and exergy analysis (ExA) have been employed separately or in conjunction to optimize energy recovery and minimize the work potential losses (exergy loss).
This paper demonstrates the effectiveness of a developed algorithm that handle the impact of ∆Tmin on energy and exergy targets in an automatic manner through a set of scripts. The scripts manipulate input data and intermediate data through loops in order to quantify and determine different energetic and exergetic quantities. The developed algorithm is testified using a literature case study in order to prove its validity. For δTmin in range [0,10] and step s =2, the algorithm performs the calculations for each δTmin in range ∆Tmin. The obtained results include the pinch analysis parameters such as the global pinch point temperature [Tpinch] as well as the minimum heating and cooling requirements ([Uhot] and [Ucool]). For the scripts devoted to the exergy concept, the algorithm determines all the exergy targets (rejection, requirement and avoidable losses). As a result for δTmin in ∆Tmin, the process external utilities Uhot and Ucool increased simultaneously from 6.85 and 4.39 MW to 12.2 and 9.75 MW with increment of δTmin, which means that the energy recovery and avoidable exergy losses reduced with respect to δTmin. For the exergy requirement and rejection targets, they increased simultaneously from 2.6602 and 1.3231 MW to 6.711 and 2.88 MW with δTmin increment, indicating the opportunity to design a system to recover work through turbine expansion. In addition to the originality of the interconnected scripts, the obtained results are in accordance with those in the literature, indicating the applicability of the developed algorithm

Keywords

References

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International Journal of Supply and Operations Management
Volume 10, Issue 4
November 2023
Pages 417-438

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