Abstract
Thermoelectric generators (TEGs) present a promising avenue for capturing waste heat from photovoltaic (PV) panels in a hybrid concentrated photovoltaic thermoelectric (CPV-TE) setup. However, advancements in CPV-TE technology, especially in optimizing design parameters, remain crucial. A comprehensive thermodynamic analysis reveals non-monotonic, coupling influences of design factors on system performances. In light of this, we tackle a multi-criteria optimization problem using the Student Psychology-Based Optimization (SPBO) algorithm with an external archive strategy. This approach successfully identifies a range of alternative (Pareto frontier) solutions in a three-objective optimization scenario. Results indicate that setting grid density and repertoire number to 10 and 100, respectively, ensures both excellent convergence and computational efficiency. Further, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method aids in selecting an energy-efficient solution from the Pareto frontier. In an efficiency-oriented strategy, total output power, overall efficiency, and TEG power generation stand at 491.32 W, 10.85 %, and 15.91 W, respectively. Conversely, prioritizing total power output yields figures of 540.9 W, 9.61 %, and 26.35 W, respectively.
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