Scenario-Based Multi-Objective Optimization of an Air-Based Building-Integrated Photovoltaic/Thermal System

In this paper, a genetic algorithm-based multi-objective optimization of a building-integrated photovoltaic/thermal (BIPV/T) system is carried out to find the best system configurations which lead to maximum energetic and exergetic performances for Kermanshah, Iran climatic condition. In the proposed BIPV/T system, the cooling potential of ventilation and exhaust airs are used in buildings for cooling the PV panels and also heating the ventilation air by heat rejection of PV panels. Four scenarios with various criteria in the form of system efficiencies and useful outputs are considered to reflect all possible useful outputs in the optimization procedure. This study models a glazed BIPV/T system with various collector areas (⁠$Apv=10,15,25,and30m2$⁠) and different length to width ratio (⁠$L/W=0.5,1,1.5,and2$⁠) to determine the optimum air mass flow rate, bottom heat loss coefficient, depth of the channel as well as the optimum depth of the air gap between PV panel and glass cover that maximize two defined objective functions in different scenarios. Results showed that using fourth scenario (with the annual total useful thermal and electrical outputs as objective functions) and first scenario (with the annual average first- and second-law efficiencies as objective functions) for optimizing the proposed BIPV/T system leads to the highest amount of useful thermal and overall outputs, respectively. Moreover, it was concluded that, if the electrical output of the system is more important than the thermal output, the first scenario gives better results.