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基于质子交换膜燃料电池的多产品能源系统的多目标优化与性能评估。

Multiobjective optimization and performance assessment of a PEM fuel cell-based energy system for multiple products.

机构信息

Prince Sattam Bin Abdulaziz University, College of Engineering, Department of Electrical Engineering, Alkharj, 11942, Saudi Arabia.

Department of Mining Engineering, Aditya Engineering College, Surampalem, Andhra Pradesh, 533437, India.

出版信息

Chemosphere. 2023 Oct;337:139348. doi: 10.1016/j.chemosphere.2023.139348. Epub 2023 Jun 26.

Abstract

In this article, the optimal design of a novel multi-generation system for the production of electricity, cooling, heat and freshwater is discussed. In this system, a Proton exchange membrane fuel cell (PEM FC) is used to generate electricity, and the heat produced by it is absorbed by the Ejector Refrigeration Cycle (ERC) and used to provide cooling and heating capacity. A reverse osmosis (RO) desalination system is also used to supply freshwater. The esign variables in this research are operating temperature and pressure and current density of FC, as well as the operating pressure of the HRVG, evaporator, and condenser of the ERC system. In order to optimize the considered system, the exergy efficiency and total cost rate (TCR) of the system are considered as optimization objective functions. To this end, the genetic algorithm (GA) is used and the Pareto front is extracted. Also, three refrigerants R134a, R600 and R123 areused as ERC system refrigerant and their performance are evaluated. Finally, the optimal design point is selected. At the mentioned point, the exergy efficiency is 70.2% and the TCR of the system is 1.78 S/h.

摘要

本文讨论了一种新型多代系统的优化设计,用于发电、制冷、供热和淡水生产。在该系统中,采用质子交换膜燃料电池(PEMFC)发电,其产生的热量被喷射式制冷循环(ERC)吸收,用于提供冷却和供暖能力。反渗透(RO)脱盐系统也用于供应淡水。本研究的设计变量为 FC 的工作温度和压力以及电流密度,以及 HRVG、蒸发器和 ERC 系统冷凝器的工作压力。为了优化所考虑的系统,将系统的火用效率和总费用率(TCR)作为优化目标函数。为此,使用遗传算法(GA)提取 Pareto 前沿。此外,还使用了三种制冷剂 R134a、R600 和 R123 作为 ERC 系统制冷剂,并对其性能进行了评估。最后,选择了最佳设计点。在该点,系统的火用效率为 70.2%,系统的 TCR 为 1.78 S/h。

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