Abstract
With more extensive applications of supercritical carbon dioxide in the design of thermal systems, it becomes necessary to explore the methods for handling measurement errors and evaluating the thermo-economical performance of the systems in the actual operations. The paper takes the supercritical carbon dioxide recompression cycle thermal system as the research object, and proposes an iterative data reconciliation algorithm that can solve the unknown variables as well as their uncertainties. The algorithm is applied for the exergy analysis of the thermal system. The analysis results on 10 groups of working conditions with random errors and 5 other groups with instrument faults show that the method proposed in the paper can effectively reduce the residuals of system constraints and measurement deviations from the sensors, decrease the calculation errors of the units’ exergy losses, and therefore increase the accuracy of the system thermal economy figures. Through data reconciliation, the errors of round trip thermal efficiency and exergy efficiency of the system can be reduced from a peak of 14.65% down to 1.04%, which proves that data reconciliation method is capable for improving the accuracy in evaluating the operational state of real thermal systems.
| Translated title of the contribution | 基于数据协调的超临界二氧化碳再压缩循环㶲分析方法 |
|---|---|
| Original language | English |
| Pages (from-to) | 9280-9291 |
| Number of pages | 12 |
| Journal | Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering |
| Volume | 45 |
| Issue number | 23 |
| DOIs | |
| State | Published - Dec 2025 |
Keywords
- data reconciliation
- exergy analysis
- recompression cycle
- redundant measurements
- supercritical carbon dioxide (S-CO)
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