Multi-objective optimization of a low temperature thermoelectric generation system with variable material properties and air gap heat dissipation based on energy, economic and environmental analysis method

Using thermoelectric generation to recover low-temperature thermal energy for power generation is an important topic of thermal optimization. In this study, energy, economic, and environmental analysis of a low-temperature thermoelectric generator system (LTTEG) is analyzed. A numerical model considering variable material properties, Thomson heat, and air gap heat dissipation effects is established for LTTEG. A genetic algorithm is applied for the multi-objective optimization of LTTEG. Key operating conditions and geometrical parameters such as the inlet flow rate, thermoelectric leg geometry, and fin geometry are selected as decision variables. Net output power, net efficiency, savings-to-investment ratio (SIR), and the year achieving zero carbon emissions (YCO2) are considered as optimization objectives (objective functions). The linear weighted evaluation method is proposed for the objective function. The results show a contradictory relationship among the objective functions. The multi-objective optimization of LTTEG is performed when the hot source is within 50–100oC, and the optimal design is obtained. Compared with the previous design, the net output power, net power generation efficiency, and SIR performance can be improved by 18.1–159.5 %, 0.4–95.8 %, and 6.0–145.5 %, respectively. Meanwhile, YCO2 decreased by 21.0–66.5 %. The multi-objective optimization method based on the genetic algorithm is beneficial to improving the comprehensive performance of LTTEG.