A real-time algorithm for the determination of R744 systems optimal high pressure.

Abstract In this paper the optimal energy efficiency and high pressure problem in single stage transcritical carbon dioxide vapour compression units is addressed. A real-time model-based optimisation algorithm for the optimal (or quasi-optimal, close to the optimal) pressure determination is developed as a more efficient and robust solution than literature approximated ones. The problem is solved by a model estimating the system performance and by measuring its boundary conditions. The model is obtained by an on-line artificial neural network identification technique and the optimisation problem is worked out by a particle swarm technique. The proposed algorithm is dynamically tested by simulation, considering the performance of a supply water temperature controlled carbon dioxide heat pump. It appears to successfully approximate the optimal cycle discharge pressure showing an average daily pressure deviation of 0.9 × 105 Pa over a two years simulation period, corresponding to 1.1% increase in the cumulated energy consumption, compared to the optimal pressure solution.

[1]  Friedrich Kauf,et al.  Determination of the optimum high pressure for transcritical CO2-refrigeration cycles , 1999 .

[2]  Marco Corradi,et al.  Optimisation of the throttling system in a CO2 refrigerating machine , 2003 .

[3]  Niels Kjølstad Poulsen,et al.  Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner’s Handbook , 2000 .

[4]  Shengming Liao,et al.  A correlation of optimal heat rejection pressures in transcritical carbon dioxide cycles , 2000 .

[5]  Jahar Sarkar,et al.  Natural refrigerant-based subcritical and transcritical cycles for high temperature heating , 2007 .

[6]  Marco Corradi,et al.  An Assessment of Heat Transfer through Fins in a Fin-and-Tube Gas Cooler for Transcritical Carbon Dioxide Cycles , 2007 .

[7]  Marco Corradi,et al.  Thermodynamic analysis of different two-stage transcritical carbon dioxide cycles , 2009 .

[8]  James Kennedy,et al.  Particle swarm optimization , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

[9]  Silvia Minetto,et al.  CO2 heat pump for domestic hot water. , 2008 .

[10]  Jostein Pettersen,et al.  Fundamental process and system design issues in CO2 vapor compression systems , 2004 .

[11]  Ciro Aprea,et al.  Heat rejection pressure optimization for a carbon dioxide split system: An experimental study , 2009 .

[12]  G. Lorentzen Revival of carbon dioxide as a refrigerant , 1994 .

[13]  Junjie Gu,et al.  The optimum high pressure for CO2 transcritical refrigeration systems with internal heat exchangers , 2005 .

[14]  Petter Nekså,et al.  CO2 heat pump systems , 2002 .

[15]  Jahar Sarkar,et al.  Optimization of a transcritical CO2 heat pump cycle for simultaneous cooling and heating applications , 2004 .

[16]  M. J. D. Powell,et al.  Restart procedures for the conjugate gradient method , 1977, Math. Program..

[17]  Marco Corradi,et al.  A critical approach to the determination of optimal heat rejection pressure in transcritical systems , 2010 .

[18]  Haruhisa Inokuty Approximate Graphical Method of Finding Compression Pressure of CO_2 Refrigerating Machine for Max. Coefficient of Performance , 1923 .

[19]  Marco Corradi,et al.  Carbon dioxide as refrigerant for tap water heat pumps: A comparison with the traditional solution , 2005 .

[20]  Ramón Cabello,et al.  Experimental evaluation of the energy efficiency of a CO2 refrigerating plant working in transcritical conditions , 2008 .

[21]  Chun-Lu Zhang,et al.  A correlation-free on-line optimal control method of heat rejection pressures in CO2 transcritical systems , 2011 .

[22]  Jeng-Shyang Pan,et al.  An improved vector particle swarm optimization for constrained optimization problems , 2011, Inf. Sci..