Modeling the cleaning cycle dynamics for air cooling condensers of thermal power plants: Optimization and global sensitivity analysis
<p>The air-cooled condenser (ACC) technology drives the decoupling of China’s water consumption and energy production. However, the optimal cleaning frequency of the ACC system has yet to be thoroughly studied. We develop a theoretical model for the total cost of the dust-fouling energy loss a...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Tsinghua University Press
2023-09-01
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| Series: | Journal of Intelligent Construction |
| Subjects: | |
| Online Access: | https://www.sciopen.com/article/10.26599/JIC.2023.9180023 |
| Summary: | <p>The air-cooled condenser (ACC) technology drives the decoupling of China’s water consumption and energy production. However, the optimal cleaning frequency of the ACC system has yet to be thoroughly studied. We develop a theoretical model for the total cost of the dust-fouling energy loss and direct cleaning service costs. This extended model is the first to consider energy loss in the cleaning and production phases with field validation. The cleaning period is optimized to minimize the total cost. Numerical solutions are sought to demonstrate the relationship between the normalized optimized cleaning period and the dimensionless inputs. An empirical fitting equation is developed for convenient use in industrial applications. An innovative variance-based global sensitivity analysis (SA) is performed to estimate the sensitivity of the optimization result to the input parameters. We found that heat resistance (<italic>R</italic><sub>f</sub>), installed capacity, utilization rate, grid electricity price (<italic>E</italic><sub>net</sub>), and cleaning cost rate have substantial impacts. The present study has the potential to improve the cleaning service plan of the onsite maintenance, to provide a theoretical framework for the life cycle analysis of the power plant, and to inform the decision-makers of the priority of data collection and sensor network deployment.</p> |
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| ISSN: | 2958-3861 2958-2652 |