This article focuses on the optimization of ORCs for heat recovery from heavy duty Internal Combustion Engines (ICEs), with particular attention to the optimal fluid selection. We considered two different ICEs featuring same power (10 MW) but different architectures: a two-stroke engine with exhaust temperature 250°C and a four-stroke engine with 350°C exhaust temperature. The analysis tackles the optimization of the heat integration between heat sources and ORC, the optimization of the cycle variables as well as the selection of the working fluid. In addition to conventional pure substances, such as hydrocarbons, refrigerants, and siloxanes, and recently synthesized refrigerants, (i.e., HFOs, HCFOs, and HFEs), also binary zeotropic mixtures have been considered. The optimization algorithm combines the evolutionary optimization algorithm PGS-COM with a systematic heat integration methodology which maximizes the heat recovered from the available heat sources. The methodology allows optimizing also the mixture composition. In total 36 pure fluids and 36 mixtures have been evaluated. HCFO-1233zde turns out to be the best or second best fluid for most cases. Cyclopentane is the best fluid for the engine with high exhaust temperature. Another promising fluid is NovecTM 649. The optimal cycles are supercritical with T-s diagrams resembling the ideal triangular cycle. The use of the mixtures leads to an increase of the exergy efficiency of around 2.5 percentage points (about 3.5 percentage point increase in net power output). Since the optimal cycle is supercritical, the temperature glide can be exploited only in condensation and, as a result, the advantage of mixtures compared to pure fluids is lower than the values reported in the literature.

Thermodynamic Optimization of heat recovery ORCs for heavy duty Internal Combustion Engine: pure fluids vs. zeotropic mixtures

INVERNIZZI, Costante Mario;
2017-01-01

Abstract

This article focuses on the optimization of ORCs for heat recovery from heavy duty Internal Combustion Engines (ICEs), with particular attention to the optimal fluid selection. We considered two different ICEs featuring same power (10 MW) but different architectures: a two-stroke engine with exhaust temperature 250°C and a four-stroke engine with 350°C exhaust temperature. The analysis tackles the optimization of the heat integration between heat sources and ORC, the optimization of the cycle variables as well as the selection of the working fluid. In addition to conventional pure substances, such as hydrocarbons, refrigerants, and siloxanes, and recently synthesized refrigerants, (i.e., HFOs, HCFOs, and HFEs), also binary zeotropic mixtures have been considered. The optimization algorithm combines the evolutionary optimization algorithm PGS-COM with a systematic heat integration methodology which maximizes the heat recovered from the available heat sources. The methodology allows optimizing also the mixture composition. In total 36 pure fluids and 36 mixtures have been evaluated. HCFO-1233zde turns out to be the best or second best fluid for most cases. Cyclopentane is the best fluid for the engine with high exhaust temperature. Another promising fluid is NovecTM 649. The optimal cycles are supercritical with T-s diagrams resembling the ideal triangular cycle. The use of the mixtures leads to an increase of the exergy efficiency of around 2.5 percentage points (about 3.5 percentage point increase in net power output). Since the optimal cycle is supercritical, the temperature glide can be exploited only in condensation and, as a result, the advantage of mixtures compared to pure fluids is lower than the values reported in the literature.
2017
2017
Ateneo di appartenenza
PE8_6 Energy systems (production, distribution, application)
Esperti anonimi
Inglese
Internazionale
STAMPA
129
168
175
8
ORC, Numerical optimization, Heat recovery, Heavy duty Internal Combustion Engine, Zeotropic mixtures
http://www.sciencedirect.com/science/article/pii/S187661021733953X
no
4
info:eu-repo/semantics/article
262
Scaccabarozzi, Roberto; Tavano, Michele; Invernizzi, Costante Mario; Martelli, Emanuele
1 Contributo su Rivista::1.1 Articolo in rivista
none
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/500471
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