TY - JOUR
T1 - Multi-criteria decision support system of the photovoltaic and solar thermal energy systems using the multi-objective optimization algorithm
AU - Kim, Jimin
AU - Hong, Taehoon
AU - Jeong, Jaemin
AU - Koo, Choongwan
AU - Jeong, Kwangbok
AU - Lee, Minhyun
N1 - Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT; Ministry of Science, ICT) (No. NRF-2018R1A5A1025137).
Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT; Ministry of Science, ICT) (No. NRF-2018R1A5A1025137 ).
Publisher Copyright:
© 2018 Elsevier B.V.
PY - 2019/4/1
Y1 - 2019/4/1
N2 - When the photovoltaic (PV) and solar thermal energy (STE) systems, which share the rooftop area, are installed in the same building, a trade-off problem occurs in terms of the energy, economic, and environmental aspects, and thus, steps need to solve this problem. Therefore, this study aimed to develop a multi-criteria decision support system of the PV and STE systems using the multi-objective optimization algorithm. This system was developed in the following six steps: (i) database establishment; (ii) designing the variables of the PV and STE systems; (iii) development of the analysis engine of the PV and STE systems; (iv) environmental and economic assessment from the life cycle perspective; (v) integrated multi-objective optimization (iMOO) with a genetic algorithm; and (vi) establishment of a multi-criteria decision support system. To verify the robustness and reliability of the developed model, an analysis of “D” City Hall and “I” Airport as target facilities was performed. The optimal PV and STE systems that consider the energy, economic, and environmental aspects at the same time were determined with respect to the 1.23 × 10 15 and 1.05 × 10 16 installation scenarios, respectively, in terms of effectiveness. The iMOO scores of the existing PV and STE systems installed in “D” City Hall and “I” Airport were 0.358 and 0.346, respectively, whereas those of the optimal solutions were 0.249 and 0.280, showing score improvements. In terms of efficiency, the times required for determining the optimal solutions were 20 and 30 min, respectively. The developed model makes the final decision-maker to find the optimal solution in introducing the PV and STE systems in the early design phase at the same time.
AB - When the photovoltaic (PV) and solar thermal energy (STE) systems, which share the rooftop area, are installed in the same building, a trade-off problem occurs in terms of the energy, economic, and environmental aspects, and thus, steps need to solve this problem. Therefore, this study aimed to develop a multi-criteria decision support system of the PV and STE systems using the multi-objective optimization algorithm. This system was developed in the following six steps: (i) database establishment; (ii) designing the variables of the PV and STE systems; (iii) development of the analysis engine of the PV and STE systems; (iv) environmental and economic assessment from the life cycle perspective; (v) integrated multi-objective optimization (iMOO) with a genetic algorithm; and (vi) establishment of a multi-criteria decision support system. To verify the robustness and reliability of the developed model, an analysis of “D” City Hall and “I” Airport as target facilities was performed. The optimal PV and STE systems that consider the energy, economic, and environmental aspects at the same time were determined with respect to the 1.23 × 10 15 and 1.05 × 10 16 installation scenarios, respectively, in terms of effectiveness. The iMOO scores of the existing PV and STE systems installed in “D” City Hall and “I” Airport were 0.358 and 0.346, respectively, whereas those of the optimal solutions were 0.249 and 0.280, showing score improvements. In terms of efficiency, the times required for determining the optimal solutions were 20 and 30 min, respectively. The developed model makes the final decision-maker to find the optimal solution in introducing the PV and STE systems in the early design phase at the same time.
KW - Environmental and economic assessment
KW - Genetic algorithm
KW - Photovoltaic system
KW - Rooftop
KW - Solar thermal energy system
KW - Trade-off problem
UR - http://www.scopus.com/inward/record.url?scp=85059467404&partnerID=8YFLogxK
U2 - 10.1016/j.scitotenv.2018.12.387
DO - 10.1016/j.scitotenv.2018.12.387
M3 - Journal article
C2 - 31096325
AN - SCOPUS:85059467404
SN - 0048-9697
VL - 659
SP - 1100
EP - 1114
JO - Science of the Total Environment
JF - Science of the Total Environment
ER -