Abstract
This study presents an optimized modelling approach for ORC based on radial turbo-expander, where the constant expander efficiency is replaced by dynamic efficiency and is unique for each set of cycle operating conditions and working fluid properties. The model was used to identify the key variables that have significant effects on the turbine overall size. These parameters are then included in the optimization process using genetic algorithm to minimize the turbine overall size for six organic fluids. Results showed that, dynamic efficiency approach predicted considerable differences in the turbine efficiencies of various working fluids at different operating conditions with the maximum difference of 7.3% predicted between the turbine efficiencies of n-pentane and R245fa. Also, the optimization results predicted that minimum turbine overall size was achieved by R236fa with the value of 0.0576m. Such results highlight the potential of the optimized modeling technique to further improve the performance estimation of ORC and minimize the size.
Original language | English |
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Pages (from-to) | 860-866 |
Journal | Energy Procedia |
Volume | 75 |
DOIs | |
Publication status | Published - 1 Aug 2015 |
Event | The 7th International Conference on Applied Energy – ICAE2015 - Abu Dhabi, United Arab Emirates Duration: 28 Mar 2015 → 31 Mar 2015 |
Keywords
- Organic Rankine cycle
- radial turbo-expander
- mean-line modeling
- genetic algorithm
- optimization