journal article·2024-12-30Open access

Parameter Correction on Waste Heat Recovery System of a Gas Turbine Using Supercritical CO2 Based on Data Reconciliation

Liang Xu, Jiarui You, Jiahua Wu, Yikang Liu, Di Zhang

Applied Sciences· Volume 15· Issue 1

Abstract

At present, the research significance of a waste heat recovery system of a gas turbine using CO2 is gradually becoming prominent, and accurate parameter measurement and performance monitoring are very necessary in the process of establishing coupled circulation system and actual operation. In this paper, a data reconciliation model is established based on the waste heat recovery system of a gas turbine using supercritical CO2 (S-CO2) cycle with two S-CO2 turbines, and several random errors and gross errors are added to verify the data reconciliation ability of the model. The calculation shows that the data reconciliation model established in this paper can obviously reduce the overall deviation level of each parameter in the thermal system, and can also identify and eliminate gross errors in the system. For some of the key parameters such as the total mass flow of CO2, data deviation is reduced to less than 1%, and high-precision power values of the equipment are calculated. This means that the measurement accuracy is effectively improved. In general, this paper makes a new attempt to use data reconciliation in parameter measurement and correction of a simple coupled cyclic system, and provides a certain reference for the subsequent application.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Thermodynamic and Exergetic Analyses of Power and Cooling Systems · Heat transfer and supercritical fluids · Refrigeration and Air Conditioning Technologies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China

Funding

University Joint Program of Shaanxi Province Key Research Project—Major Project · the Major Project of Shaanxi Province Key Research Project

References (38)

Show source-provided references
1. A Summary of wearable textiles power generation10.1088/1742-6596/1792/1/012037 ↗
2. (2024). EI Statistical Review of World Energy 2024, Energy Institute.
3. Advanced gas turbine cycles for power generation: A critical review10.1016/S1359-4311(97)00116-6 ↗
4. Étude on gas turbine combined cycle power plant—Next 20 years10.1115/1.4031477 ↗
5. Comparative study of alternative ORC-based combined power systems to exploit high temperature waste heat10.1016/j.enconman.2014.10.020 ↗
6. Dynamic characteristics of a direct-heated supercritical carbon-dioxide Brayton cycle in a solar thermal power plant10.1016/j.energy.2012.11.029 ↗
7. Genetically tuned fuzzy PID controller in two area reheat thermal power system10.3103/S1068371216100047 ↗
8. Control of supercritical organic Rankine cycle based waste heat recovery system using conventional and fuzzy self-tuned PID controllers10.1007/s12555-018-0766-6 ↗
9. Operational Optimisation of a Heat Pump System with Sensible Thermal Energy Storage using Genetic Algorithm: A Case Study10.2298/TSCI171231272S ↗
10. Optimization design of heat recovery systems on rotary kilns using genetic algorithms10.1016/j.apenergy.2017.05.072 ↗
11. Genetic algorithm multiobjective optimization of a thermal system with three heat transfer enhancement characteristics10.1615/JEnhHeatTransf.2020032595 ↗
12. A study on the optimal air, load and source side temperature combination for a variable air and water volume ground source heat pump system10.1016/j.applthermaleng.2020.115595 ↗
13. Shankar, N., and Jordache, C. (1999). Data Reconciliation and Gross Error Detection: An Intelligent Use of Process Data, Elsevier.
14. Romagnoli, J.A., and Sánchez, M.C. (1999). Data Processing and Reconciliation for Chemical Process Operations, Elsevier.
15. Observability and redundancy classification in multicomponent process networks10.1002/aic.690330110 ↗
16. Reconciliation of process flow rates by matrix projection. Part I: Linear case10.1002/aic.690290602 ↗
17. Reconciliation of process flow rates by matrix projection. Part II: The nonlinear case10.1002/aic.690320410 ↗
18. Swartz, C.L.E. (1989, January 9–14). Data reconciliation for generalized flowsheet applications. Proceedings of the ACS National Meeting, Dallas, TX, USA.
19. Reilly, P.M., and Carpani, R.E. (1963, January 23). Application of statistical theory of adjustment to material balances. Proceedings of the 13th Canadian Chemical Engineering Congress, Montreal, QC, Canada.
20. Detection of gross errors in process data10.1002/aic.690280519 ↗
21. Generalized likelihood ratio method for gross error identification10.1002/aic.690330911 ↗
22. Generalized likelihood ratios for gross error identification in dynamic processes10.1002/aic.690340810 ↗
23. Reconciliation of mass flow rate measurements in a chemical extraction plant10.1002/cjce.5450670411 ↗
24. Data reconciliation for chemical reaction systems using vessel extents and shape constraints10.1016/j.compchemeng.2017.02.003 ↗
25. Heat exchanger network simulation, data reconciliation & optimization10.1016/j.applthermaleng.2012.11.033 ↗
26. Steady-state data reconciliation for absorption refrigeration systems10.1016/j.applthermaleng.2012.10.027 ↗
27. Magnus, L., and Jansky, J. (2002, January 15–16). Process data reconciliation in nuclear power plants. Proceedings of the EPRI Nuclear Power Performance Improvement Seminar, Saratoga Springs, NY, USA.
28. Power recapture and power uprate in NPPS with process data reconciliation in accordance with VDI 2048
29. Data reconciliation and fault detection by means of plant-wide mass and energy balances10.1016/S0149-1970(03)00015-5 ↗
30. Simultaneous model selection, robust data reconciliation and outlier detection with swarm intelligence in a thermal reactor power calculation10.1016/j.anucene.2011.06.001 ↗
31. Model-based data reconciliation to improve accuracy and reliability of performance evaluation of thermal power plants
32. Data reconciliation and gross error detection for operational data in power plants10.1016/j.energy.2014.03.024 ↗
33. The implementation of the data validation process in a gas turbine performance monitoring system
34. A simple mathematical approach to data reconciliation in a single-shaft combined cycle system10.1115/1.2978994 ↗
35. Energy, exergy and exergoeconomic analysis of two supercritical CO2 cycles for waste heat recovery of gas turbine10.1016/j.applthermaleng.2021.117337 ↗
36. (2017). VDI-2048: Control and Quality Improvement of Process Data and Their Uncertainties by Means of Correction Calculation for Operation and Acceptance Tests, VDI Verein Deutscher Ingenieure. Association of German Engineers.
37. Exploration on the comprehensive data reconciliation framework for unknown parameter inference in the nuclear power plant system10.1016/j.applthermaleng.2024.123138 ↗
38. Finding megawatts in nuclear power plants with process data reconciliation10.1115/ICONE12-49152 ↗