TY - JOUR
T1 - Exergetic-Economic analysis and optimization of solar assisted heat pump using Multi-objective Genetic Algorithm
AU - Nasruddin,
AU - Alhamid, M. I.
AU - Aisyah, N.
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2018/1/25
Y1 - 2018/1/25
N2 - This study proposes the use of two-stage heat pump systems (SAHPs) for high temperature applications, 105°C. This system integrates solar thermal collectors and heat pumps into a hybrid system to meet the 400 kW heating load. The aim of this research is providing a method to deliver heat with sustainable energy resource, than to improve the performance of the system which is indicated by low exergy destruction. The model creation, performance evaluation and the optimization of solar assisted heat pump system are discussed in this paper. This system used R1234ze (E) as working fluid. A genetic algorithm is employed to optimize operation condition of the system. To ensure that the optimal solution obtained from the proposed method is an optimum condition, three constraints are selected, including evaporation temperatures, condensing temperatures and compressor temperatures while exergy destruction and total cost as the objective functions. The result showed that the system has an optimum condition at evaporating temperature of 317 K, Flash Tank temperature of 353.6 K and condensing temperature of 380.4 K with exergy destruction of 70.21 kW and total cost of 63,441 US$.
AB - This study proposes the use of two-stage heat pump systems (SAHPs) for high temperature applications, 105°C. This system integrates solar thermal collectors and heat pumps into a hybrid system to meet the 400 kW heating load. The aim of this research is providing a method to deliver heat with sustainable energy resource, than to improve the performance of the system which is indicated by low exergy destruction. The model creation, performance evaluation and the optimization of solar assisted heat pump system are discussed in this paper. This system used R1234ze (E) as working fluid. A genetic algorithm is employed to optimize operation condition of the system. To ensure that the optimal solution obtained from the proposed method is an optimum condition, three constraints are selected, including evaporation temperatures, condensing temperatures and compressor temperatures while exergy destruction and total cost as the objective functions. The result showed that the system has an optimum condition at evaporating temperature of 317 K, Flash Tank temperature of 353.6 K and condensing temperature of 380.4 K with exergy destruction of 70.21 kW and total cost of 63,441 US$.
UR - http://www.scopus.com/inward/record.url?scp=85041685786&partnerID=8YFLogxK
U2 - 10.1088/1755-1315/105/1/012064
DO - 10.1088/1755-1315/105/1/012064
M3 - Conference article
AN - SCOPUS:85041685786
SN - 1755-1307
VL - 105
JO - IOP Conference Series: Earth and Environmental Science
JF - IOP Conference Series: Earth and Environmental Science
IS - 1
M1 - 012064
T2 - 2nd International Tropical Renewable Energy Conference, i-TREC 2017
Y2 - 3 October 2017 through 4 October 2017
ER -