This article presents a novel solution to enhance the performance and cost-effectiveness of a biomass-based proton exchange membrane (PEM) fuel cell. It investigates the proposed configuration from energy, exergy, economic, and environmental aspects. The idea is conducted by the integration of the proposal with a gasifier, multi-effect desalination (MED) unit, and the series two-stage organic Rankine cycle (STORC) using various zeotropic mixtures for the use of waste heat for heat, power, and freshwater production. A comparative parametric study is carried out not only to evaluate the effect of main parameters on the performance of the proposed system but also to find the best zeotropic mixture from different standpoints. Also, the tri-objective optimization using a genetic algorithm approach is implemented to the system to ascertain the best operating condition for low total cost rate and high exergy efficiency and produced fresh water simultaneously. The results of a comparative parametric study reveal the superiority of R601a-C₂Butene (75-25) among various STORC working fluids from thermodynamic and economic points of view. The results further show that the proposed integrated system has a considerably lower CO₂ index compared to the same system without the STORC unit. For the final tri-objective optimization point, while the minimum total cost rate is 64.91 $/h, the maximum exergy efficiency and produced freshwater is 23.43% and 162.86 m³/day, respectively. Furthermore, the scatter distribution of the main decision variable reveals that moisture content and current density are not a sensible variable, and their optimal points are distributed in the whole domain.

本文提出了一种新的解决方案，以增强基于生物质的质子交换膜（PEM）燃料电池的性能和成本效益。它从能源，火用，经济和环境方面研究了建议的配置。通过将提案与气化器，多效脱盐（MED）装置以及使用各种共沸混合物的两级有机朗肯循环（STORC）集成在一起，利用余热来利用余热产生热量，功率，和淡水生产。进行了比较参数研究，不仅评估了主要参数对所提出系统性能的影响，而且还从不同角度寻找了最佳的共沸混合物。也，对系统实施了使用遗传算法的三目标优化，以确保最佳的运行条件，从而降低总成本率，提高火用效率并同时生产淡水。比较参数研究的结果显示了R601a-C的优越性从热力学和经济角度考虑，在各种STORC工作流体中使用₂丁烯（75-25）。结果进一步表明，与没有STORC单元的相同系统相比，所提出的集成系统的CO ₂指数要低得多。对于最终的三目标优化点，虽然最低总成本率为64.91 $ / h，但最大火用效率和产出淡水分别为23.43％和162.86 m ³ / day。此外，主要决策变量的散布分布表明，水分含量和电流密度不是一个明智的变量，它们的最佳点分布在整个域中。