TY - JOUR
T1 - An integrated multi-objective optimization model for determining the optimal solution in implementing the rooftop photovoltaic system
AU - Koo, Choongwan
AU - Hong, Taehoon
AU - Lee, Minhyun
AU - Kim, Jimin
N1 - Publisher Copyright:
© 2015 Elsevier Ltd. All rights reserved.
PY - 2016/5
Y1 - 2016/5
N2 - The photovoltaic (PV) system has been highlighted as a sustainable clean energy source. To successfully implement the PV system in a real project, several impact factors should be simultaneously considered. This study aimed to develop an integrated multi-objective optimization (iMOO) model for determining the optimal solution in implementing the rooftop PV system. This study was conducted in six steps: (i) establishment of database; (ii) generation of the installation scenarios in the rooftop PV system; (iii) energy simulation using the software program 'RETScreen'; (iv) economic and environmental assessment from the life cycle perspective; (v) establishment of the iMOO process using a genetic algorithm; and (vi) systemization of the iMOO model using a Microsoft-Excel-based VBA. Two criteria were used to assess the robustness and reliability of the developed model. In terms of effectiveness, the optimal solution was determined from a total of 399,883,120 (=91×49×19×80×59) possible scenarios by comprehensively considering various factors. In terms of efficiency, it was concluded that the time required for determining the optimal solution was 150 s. The developed model makes it possible for final decision-maker such as construction managers or contractors to determine the optimal solution in implementing the rooftop PV system in the early design phase.
AB - The photovoltaic (PV) system has been highlighted as a sustainable clean energy source. To successfully implement the PV system in a real project, several impact factors should be simultaneously considered. This study aimed to develop an integrated multi-objective optimization (iMOO) model for determining the optimal solution in implementing the rooftop PV system. This study was conducted in six steps: (i) establishment of database; (ii) generation of the installation scenarios in the rooftop PV system; (iii) energy simulation using the software program 'RETScreen'; (iv) economic and environmental assessment from the life cycle perspective; (v) establishment of the iMOO process using a genetic algorithm; and (vi) systemization of the iMOO model using a Microsoft-Excel-based VBA. Two criteria were used to assess the robustness and reliability of the developed model. In terms of effectiveness, the optimal solution was determined from a total of 399,883,120 (=91×49×19×80×59) possible scenarios by comprehensively considering various factors. In terms of efficiency, it was concluded that the time required for determining the optimal solution was 150 s. The developed model makes it possible for final decision-maker such as construction managers or contractors to determine the optimal solution in implementing the rooftop PV system in the early design phase.
KW - Economic and environmental assessment
KW - Existing building
KW - Genetic algorithm
KW - Integrated multi-objective optimization
KW - Rooftop photovoltaic system
KW - Trade-off problem
UR - http://www.scopus.com/inward/record.url?scp=84953790167&partnerID=8YFLogxK
U2 - 10.1016/j.rser.2015.12.205
DO - 10.1016/j.rser.2015.12.205
M3 - Review article
AN - SCOPUS:84953790167
SN - 1364-0321
VL - 57
SP - 822
EP - 837
JO - Renewable and Sustainable Energy Reviews
JF - Renewable and Sustainable Energy Reviews
ER -