Importance of the reconciliation method to handle experimental data in refrigeration and power cycle: application to a reversible heat pump/organic Rankine cycle unit integrated in a positive energy building
Abstract
Abstract
Experimental data is often the result of long and costly experimentations. Many times, measurements are used directly without (or with few) analysis and treatment. This paper, therefore, presents a detailed methodology to use steady-state measurements efficiently in the analysis of a thermodynamic cycle. The reconciliation method allows to correct each measurement as little as possible, taking its accuracy into account, to satisfy all constraints and to evaluate the most probable physical state. The reconciliation method should be used for multiple reasons. First, this method allows to close energy and mass balances exactly, which is needed for predictive models. Also, it allows determining some unknowns that are not measured or that cannot be measured precisely. Furthermore, it fully exploits the collected measurements with redundancy and it allows to know which sensor should be checked or replaced if necessary. An application of this method is presented in the case of a reversible HP/ORC unit. This unit is a modified heat pump which is able to work as an organic Rankine cycle by reversing its cycle. Combined with a passive house comprising a solar roof and a ground heat exchanger, it allows to get a positive energy building. In this study case, the oil mass fraction is not measured despite its strong influence on the results. The reconciliation method allows to evaluate it. The efficiency of this method is proven by comparing the error on the outputs of steady-state models of compressor and exchangers. An example is given with the prediction of the pinch-point of an evaporator. In this case, the normalized root mean square deviation (NRMSD) is decreased from 14.3 to 4.1 % when using the reconciliation method. This paper proves that the efficiency of the method and also that the method should be considered more often when dealing with experimentation.
Keywords
- Reconciliation method,
- Experimental analysis,
- Reversible heat pump/organic Rankine cycle
References
- Kuehn and Davidson (1967) Computer control II mathematics of control (pp. 44-47)
- Hodouin and Everell (1980) A hierarchical procedure for adjustment and material balancing of mineral processed data (pp. 91-116) https://doi.org/10.1016/0301-7516(80)90002-2
- Weiss et al. (1996) Data reconciliation–an industrial case study (pp. 1441-1449) https://doi.org/10.1016/0098-1354(95)00241-3
- Heyen and Kalitvebtzeff (1997) Methodology for optimization of operation to reduce site-scale energy use in production plants (pp. 1005-1014) https://doi.org/10.1016/S1359-4311(97)00017-3
- Placido and Loureiro (1998) Industrial application of data reconciliation (pp. S1035-S11038) https://doi.org/10.1016/S0098-1354(98)00208-7
- Schladt and Hu (2008) Soft sensors based on nonlinear steady-state data reconciliation in the process industry (pp. 320-331)
- Lid and Skogestad (2008) Data reconciliation and optimal operation of a catalytic naphta reformer (pp. 320-331) https://doi.org/10.1016/j.jprocont.2007.09.002
- Bruno, J. C., Romera, S., Figueredo, G., Coronas, A.: Hybrid solar/gas Single/Double effect absorption chiller: operational results using data reconciliation. In: Proceedings of the 2nd International Conference on Solar Air-conditionning, Tarragona, pp. 244–249 2007
- Martinez-Maradiaga et al. (2013) Steady-state data reconciliation for absorption refrigeration system (pp. 1170-1180) https://doi.org/10.1016/j.applthermaleng.2012.10.027
- Szega and Nowak (2015) An optimization of redundant measurements location or thermal capacity of power unit steam boiler calculations using data reconciliation method (pp. 135-141) https://doi.org/10.1016/j.energy.2015.03.125
- Jiang et al. (2014) A, data reconciliation based framework for integrated sensor and equipment performance monitoring in power plants (pp. 270-282) https://doi.org/10.1016/j.apenergy.2014.08.040
- Cuevas, C.: Contribution to the modelling of refrigeration systems. PhD thesis, Liege, University of Liege, 2006
- Quoilin, S., Schrouff, J.: Assessing the quality of experimental data with Gaussian regression processes: Example with an injection Scroll compressor, 2014 Purdue conferences. In: Proceedings of Purdue conference, Purdue, 14–17 Jul 2014
- Prata et al. (2010) Simultaneous robust data reconciliation and gross error detection through particle swarm optimization for an industrial poplypropylene reactor (pp. 4943-4964) https://doi.org/10.1016/j.ces.2010.05.017
- Ozyurt and Pike (2004) Theory and practice of simultaneous data reconciliation gross error detection for chemical processes (pp. 381-402) https://doi.org/10.1016/j.compchemeng.2003.07.001
- Zhang et al. (2010) Quasi-weighted least squares estimator for data reconciliation (pp. 154-162) https://doi.org/10.1016/j.compchemeng.2009.09.007
- Dumont, O., Quoilin, S., Lemort, V.: Design, modelling and experimentation of a reversible HP-ORC prototype, ASME TURBO EXPO 2014. In: Proceedings of the ASME TURBO EXPO 2014, Dusseldorf, 16–20 Jun 2014
- Dumont et al. (2015) Experimental investigation of a reversible heat pump/organic Rankine cycle unit designed to be coupled with a passive house to get a Net Zero Energy Building (pp. 190-203) https://doi.org/10.1016/j.ijrefrig.2015.03.008
- Bell, I., Quoilin, S., Wronski, J., Lemort, V.: Coolprop: an open source reference-quality thermophysical property library, ORC 2015 conference, 2015,
- http://orbit.dtu.dk/ws/files/59934392/COOLPROP.pdf
- Quoilin, S.: Sustainable energy conversion through the use of organic Rankinec for waste heat recovery and solar applications. PhD thesis, Liege, University of Liege, 2011
- Lemort, V.: Contribution to the characterization of scroll machines in compressor and expander modes. PhD thesis, Liege, University of Liege, 2008
10.1007/s40095-016-0206-4