Performance prediction and working fluids selection for organic Rankine cycle under reduced temperature
| Autor: | Junaid Alvi, Chen Guibing, Qingsong An, Jun Zhao, Yongzhen Wang, Chang Nini |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Organic Rankine cycle
Exergy business.industry 020209 energy Energy Engineering and Power Technology 02 engineering and technology Quantitative correlation Industrial and Manufacturing Engineering Reduced properties 020401 chemical engineering 0202 electrical engineering electronic engineering information engineering Exergy efficiency Performance prediction Environmental science Working fluid 0204 chemical engineering Process engineering business Selection (genetic algorithm) |
| Zdroj: | Applied Thermal Engineering. 153:95-103 |
| ISSN: | 1359-4311 |
| Popis: | This paper presents the approach for selection of optimal working fluids and cycle performance prediction for organic Rankine cycle (ORC) based on a theoretical exergy efficiency model (EEM) under reduced temperature. 18 working fluids with critical temperature from 100 to 200 °C are under evaluation. When the condensing temperature is 40 °C and reduced evaporating temperature is 0.85, the maximum overall exergy efficiency will be obtained when the heat source temperature approaches to the critical temperature of working fluid. Then, the optimal working fluids are selected by overall exergy efficiency. When the heat source inlet temperatures are 130 °C, 150 °C, 170 °C and 190 °C, the optimal working fluids are R236ea, R245fa, R245ca and R365mfc, respectively. In addition, under the same entire reduced temperatures the exergy efficiencies of different working fluids tend to be approximately equal and obey the circular distributions. The quantitative correlation between the optimal reduced evaporating temperature and reduced heat source temperature is given. The correlation provides a non-dimensional method to calculate the optimal evaporating temperature for different working fluids on the target of exergy efficiency. |
| Databáze: | OpenAIRE |
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