Performance enhancement of integrated energy system using a PEM fuel cell and thermoelectric generator

火用 质子交换膜燃料电池 工艺工程 可用能 热电发电机 聚光镜(光学) 热电联产 聚合物电解质膜电解 计算机科学 环境科学 发电 汽车工程 热电效应 核工程 材料科学 功率(物理) 工程类 化学 燃料电池 热力学 电解 化学工程 物理 光学 光源 物理化学 电解质 电极
作者
Tao Hai,Kabir Al Mamun,Amjad Ali,Evgeny Solomin,Jincheng Zhou,N. Sinaga
出处
期刊:International Journal of Hydrogen Energy [Elsevier]
卷期号:51: 1280-1292 被引量:6
标识
DOI:10.1016/j.ijhydene.2023.03.442
摘要

Coupling different energy conversion systems together to have more sustainable energy systems can be a promising way to cope with the challenges of the energy consumption crisis. In the current work, an organic Rankin cycle (ORC) has been coupled with some other units like the Kalina cycle and some other subunits including a proton exchange membrane (PEM) electrolyzer, fuel cell, and thermoelectric generator (TEG). Two layouts of systems have been considered for evaluation. In the modified system to enhance the overall performance of the unit, fuel cells and a TEG have been utilized. Having analyzed the system from technical and economical viewpoints it is concluded that the proposed system has an energy and exergy efficiency of 16.77% and 61.69%, respectively. The results show that 0.0001632 mol/h of hydrogen can be produced with the electrolyzer system. The comparison of the suggested system with basic plant indicated that the suggested system generated 155.33 kW electrical power while the basic system generated 146.2 kW. Exergy examination represents that the condenser with 20.13 kW has the highest rate of exergy destruction rate. A parametric analysis has been performed for different parameters of the system and the calculation represents that the energy efficiency and overall exergy destruction rate with the defined electricity cost rate show a different behavior, which indicates the necessity of multi-objective optimization. For the improved plant according to the four parameters, multi-objective optimization has been done according to the genetic algorithm and the most optimal state of the system has been extracted based on three-objective optimization. In the optimum state, the exergy efficiency of the system and electricity cost obtained 62% and 10.72 $/h.
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