DocumentCode
559099
Title
Energy saving of combined fresh water and cold generation system by compressor intercooler waste heat recovery
Author
Janghorban, Iman ; Liu, Hongbin ; Ghorbannezhad, Payam ; Yoo, ChangKyoo
Author_Institution
Dept. of Environ. Sci. & Eng., Kyung Hee Univ., Yongin, South Korea
fYear
2011
fDate
26-29 Oct. 2011
Firstpage
317
Lastpage
322
Abstract
Fresh water and cold which are produced by desalination and cooling processes are simultaneously utilized in many factories and industries. Energy saving can be possible by integration of desalination and cooling systems. This paper contributes to a new integration scheme of the reverse osmosis (RO) and refrigeration systems. Compressor intercooler and condenser waste heat are recovered to increase the intake seawater temperature, which causes decrease in RO pump usage and compressor power consumption. The RO system and refrigeration cycle is modeled. Experimental design of central composite design (CCD) is applied to determine the input decision variables, which are consist of intercooler pressure and heat source temperature (TH) responses variables are coefficient of performance (COP) and power consumption of reverse osmosis (PRO). Multi objective optimization to minimize PRO and maximize COP is performed using genetic algorithm (GA) over the ANN model. The input decision variables corresponding to Pareto optimal sets are presented minimum as the optimal design parameters.
Keywords
desalination; design of experiments; energy conservation; genetic algorithms; heat recovery; mechanical engineering computing; neural nets; power engineering computing; pumps; reverse osmosis; waste heat; ANN model; RO pump; central composite design; cold generation system; compressor intercooler waste heat recovery; cooling processes; desalination; energy saving; experimental design; genetic algorithm; refrigeration systems; reverse osmosis; Artificial neural networks; Equations; Mathematical model; Neurons; Optimization; Power demand; Reverse osmosis; Artificial neural network; Genetic algorithm; Multi objective optimization; Refrigeration; Reverse Osmosis (RO);
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Automation and Systems (ICCAS), 2011 11th International Conference on
Conference_Location
Gyeonggi-do
ISSN
2093-7121
Print_ISBN
978-1-4577-0835-0
Type
conf
Filename
6106443
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