Multi-objective optimization for efficient modeling and improvement of the high temperature PEM fuel cell based Micro-CHP system

Fuel cells due to different useful features such as high efficiency, low pollution, noiselessness, lack of moving parts, variety of fuels used and wide range of capacity of these sources can be the main reasons for their tendency to use them in different applications. In this study, the application of a high temperature proton exchange membrane fuel cell (HT-PEMFC) in a combined heat and power (CHP) plant has been analyzed. This study presents a multi-objective optimization method to provide an optimal design parameters for the HT-PEMFC based micro-CHP during a 14,000 h lifetime by considering the effect of degradation. The purpose is to optimize the net electrical efficiency and the electrical power generation. For the optimization process, different design parameters including auxiliary to process fuel ratio, anodic stoichiometric ratio, steam to carbon ratio, and fuel partialization level have been employed. For optimization, A new technique based on Tent mapping and Levy flight mechanism, called improved collective animal behavior (ICAB) algorithm has been employed to solve the algorithm premature convergence shortcoming. Experimental results of the proposed method has been applied to the data of a practical plant (Sidera30) for analyzing the efficiency of the proposed ICAB based system, it is compared with normal condition and another genetic algorithm based method for this purpose. Final results showed that the difference between the maximum electrical power production under normal condition and ICAB based condition changes from 2.5 kW when it starts and reaches to its maximum value, 3.0 kW, after 14,000 h lifetime. It is also concluded that the cumulative average for the normal and the ICAB based algorithm are 24.01 kW and 27.04 kW, respectively which showed about 3.03 kW cumulative differences. (C) 2020 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.