TY - JOUR
DP - National Agricultural Library
DB - PubAg
JO - The Science of the total environment
TI - Multi-criteria decision support system of the photovoltaic and solar thermal energy systems using the multi-objective optimization algorithm
A1 - Kim, Jimin
A4 - Kim, Jimin
A4 - Hong, Taehoon
A4 - Jeong, Jaemin
A4 - Koo, Choongwan
A4 - Jeong, Kwangbok
A4 - Lee, Minhyun
EP - 2019 v.659
KW - airports
KW - algorithms
KW - databases
KW - economic analysis
KW - energy
KW - models
KW - multi-criteria decision making
KW - solar thermal energy
AN - 6282292
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 × 1015 and 1.05 × 1016 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.
PY - 2019
LA -
DA - 2019-04-01
VL - v. 659
SP - pp. 1100-1114
DO - 10.1016/j.scitotenv.2018.12.387
ER -