LAPSE:2023.28358
Published Article
LAPSE:2023.28358
Pinch-Based General Targeting Method for Predicting the Optimal Capital Cost of Heat Exchanger Network
Dianliang Fu, Qixuan Li, Yan Li, Yanhua Lai, Lin Lu, Zhen Dong, Mingxin Lyu
April 11, 2023
Pinch analysis is vital in optimizing heat exchanger networks (HENs). Targeting methods are used when determining cost effectiveness with pinch analysis. However, the existing targeting methods for the capital cost of HEN are not suitable for wide application scenarios. Therefore, we developed a high-accuracy general capital-cost-targeting method. It is built on a final structure that was evolved from the spaghetti structure of HEN through four loop elimination stages. This structure helps to reduce the prediction deviation of the method. To achieve high adaptability while establishing this method, we considered the different heat exchanger cost categories, different cost laws for one stream pair, and area limitations of heat exchangers that may be encountered in practice. In addition, allowing streams to use individual temperature difference contributions enhances the method’s predictive capacity. The potential defects of the method found in numerical experiments and case studies were corrected with improvement measures. As a result, the accuracy and stability of the targeting method were further enhanced, with absolute target deviations generally within 10% and often within 5%. This study provides a benchmark for the optimal capital cost of HEN, allowing for a better economic effect when applying pinch analysis.
Keywords
capital cost target, energy recovery, general method, Heat Exchanger Network, pinch analysis, spaghetti structure
Suggested Citation
Fu D, Li Q, Li Y, Lai Y, Lu L, Dong Z, Lyu M. Pinch-Based General Targeting Method for Predicting the Optimal Capital Cost of Heat Exchanger Network. (2023). LAPSE:2023.28358
Author Affiliations
Fu D: School of Energy and Power Engineering, Shandong University, Jinan 250061, China
Li Q: School of Energy and Power Engineering, Shandong University, Jinan 250061, China
Li Y: School of Energy and Power Engineering, Shandong University, Jinan 250061, China
Lai Y: School of Energy and Power Engineering, Shandong University, Jinan 250061, China
Lu L: Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hong Kong, China
Dong Z: Suzhou Research Institute, Shandong University, Suzhou 215123, China
Lyu M: School of Energy and Power Engineering, Shandong University, Jinan 250061, China; Suzhou Research Institute, Shandong University, Suzhou 215123, China
Journal Name
Processes
Volume
11
Issue
3
First Page
923
Year
2023
Publication Date
2023-03-17
Published Version
ISSN
2227-9717
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PII: pr11030923, Publication Type: Journal Article
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LAPSE:2023.28358
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doi:10.3390/pr11030923
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Apr 11, 2023
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