首页> 外文期刊>Renewable energy >Performance optimization and thermodynamic analysis of irreversibility in a contemporary solar thermoelectric generator
【24h】

Performance optimization and thermodynamic analysis of irreversibility in a contemporary solar thermoelectric generator

机译:现代太阳能热电发电机不可逆转性的性能优化与热力学分析

获取原文
获取原文并翻译 | 示例
       

摘要

In this paper, a model based on the first and second laws of thermodynamics is developed in MATLAB R2020a Simulink software and is utilized in thermodynamically optimizing a bismuth telluride based solar thermoelectric generator (STEG) while estimating all system irreversibilities. This study aims at presenting a cheaper and simpler method of optimizing the performance of traditional STEGs without using segmentation or cascading. This is achieved by studying the effects of operating thermal and electric parameters such as load-resistance ratio (LRR), optical concentration ratio (OCR), thermal concentration ratio (TCR), hot junction temperature (T-h), cold junction temperature, current and voltage on STEG power output, energy and exergy efficiencies, respectively. The results obtained are validated with experimental and numerical data from previous studies. Results indicate that for an OCR of 30, a STEG exergy efficiency of about 6.5% is obtained from a conventional bismuth-telluride single-stage module. Also, a means of maximising STEG performance while reducing system irreversibilities to the barest minimum is presented. The results obtained herein will provide useful information in the maximisation of conventional and complex STEG systems employing segmentation or cascading. (c) 2020 Elsevier Ltd. All rights reserved.
机译:本文在MATLAB R2020A Simulink软件中开发了一种基于热力学第一和第二热力学定律的模型,并且用于热力学地优化基于碲化铋的太阳能热电发电机(STEG),同时估计所有系统的不缩义。本研究旨在提出一种更便宜和更简单的方法,可以在不使用分割或级联的情况下优化传统臭椿的性能。这是通过研究操作热和电参数(例如负载抗性比(LRR),光学浓度比(OCR),热浓度比(TCR),热结温度(TH),冷结温,电流和电流和STEG功率输出的电压分别为电源,能源和漏洞效率。获得的结果用来自先前研究的实验性和数值数据验证。结果表明,对于OCR为30,从常规的碲化铋单级模块获得约6.5%的STEG漏洞效率。而且,呈现了一种最大化STEG性能的手段,同时将系统不缩义降低到最低限度的最小值。本文获得的结果将在采用分段或级联的常规和复杂的STEG系统的最大化中提供有用的信息。 (c)2020 elestvier有限公司保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号