scholarly journals Aquadest production system as steam turbine bottom cycle III: Influence of wastewater percentage and pinch point temperature difference of condenser

Author(s):  
Engkos Achmad Kosasih ◽  
Fauzan Widianto ◽  
Ahmad Alfan Farizi ◽  
Rizal Ibnu Wahid
2018 ◽  
Vol 67 ◽  
pp. 04029 ◽  
Author(s):  
E A Kosasih ◽  
R I Wahid ◽  
A A Faros

Most of the energy derived from Steam turbine is discharge in the condenser at temperatures that may damage the environment. The condenser cooling water has gone through water treatment process, so it would be better used as raw material to produce aquadest. This study simulate a system that produces aquadest by throttling 10% of cooling water that coming out the condenser into a vacuum chamber (3 kPa). The resulting cold vapoor is condensed in the evaporator become aquadest. Cold water coming out the vacuum chamber is mixed with water coming out the condenser is lower than before. Parameters that varied are the condenser pressure and pinch point temperature difference (PPTD) inside the condenser. The simulation resulted the condenser cooling water temperature of less than 40 °C (design point), especially at PPTD of 9 °C. that applicable to all variations of condenser pressure 7 to 12 [kPa]. Spesific energy consumption of aquadest are between 550,7 to 900,3 [kPa] (less than half of water evaporation heat) and the aquadest flowrate are between 0,116 to 0,319 [kg/s].


Energy ◽  
2017 ◽  
Vol 141 ◽  
pp. 97-107 ◽  
Author(s):  
Jiansheng Wang ◽  
Mengzhen Diao ◽  
Kaihong Yue

2019 ◽  
Vol 217 ◽  
pp. 798-807 ◽  
Author(s):  
Marcin Jankowski ◽  
Aleksandra Borsukiewicz ◽  
Katarzyna Szopik-Depczyńska ◽  
Giuseppe Ioppolo

Author(s):  
Mahmood Mohagheghi ◽  
Jayanta Kapat

Supercritical carbon dioxide (S-CO2) Brayton cycle represents significant advantages in solar tower application. Various configurations of S-CO2 Brayton cycle employing recuperation, recompression, intercooling and reheating have been investigated. The thermodynamic performance of each cycle configuration is optimized by using Genetic Algorithm in which the maximum cycle efficiency is defined as the objective function. The optimization process is comprehensive, i.e., the decision variables such as temperature and pressure of turbines, compressors, re-heaters, inter-coolers, and the pinch point temperature difference are optimized simultaneously. The recompression inlet temperature and mass flow fraction are also optimized along with other decision variables where that is the case. The main limiting factors in the optimization process are maximum cycle temperature, minimum heat rejection temperature, and pinch point temperature difference. The maximum cycle pressure is also a limiting factor in all studied cases except the simple recuperated cycle. The optimized cycle efficiency can vary from 55.77% to 62.02% where the highest value is obtained for the recompression recuperated cycle with reheating and intercooling. The optimization is based on thermodynamic analysis only, even though decision making for practical systems should be based on thermo-economic optimization.


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