Multi-objective optimization of thermo-electric heat pump using genetic algorithm and fuzzy Bellman-Zadeh decision making

An exo-reversible two-stage thermoelectric heat pump is thermodynamically optimized in consideration of finite time thermodynamics and multi-objective optimization using non-dominated sorted genetic algorithm (NSGA) approaches. The two stages of thermoelectric heat pump are assumed to be in electrically series configuration and only internal irreversibilities for the above mentioned system has been taken into consideration. Heating capacity (Qh) and Coefficient of Performance (COP) of the system are taken as dual objective functions, which are derived by FTT approach. These two objectives are maximized concurrently using NSGA. Authors have considered five decision variables as working electric current (I), number of thermoelectric element pairs at the top and bottom stage as n and m, heat source temperature (T_h) and heat sink temperature (T_c) for multi-objective optimization of thermoelectric heat pump. MATLAB environment is used to obtain the Pareto Optimal frontier between COP and heating capacity and their best optimal values are selected by Bellman-Zadeh decision making technique. A comparative analysis of single objective and dual objective optimization of aforementioned objectives has been carried out along with along with the effect of various performance parameters on dual objective analysis are discussed and presented graphically.