Mathematical modelling, performance evaluation and exergy analysis of a hybrid photovoltaic/thermal-solar thermoelectric system integrated with compound parabolic concentrator and parabolic trough concentrator

抛物线槽 光伏系统 热的 选矿厂 火用 材料科学 可用能 热电发电机 热电效应 计算机科学 机械工程 环境科学 工艺工程 物理 电气工程 热力学 工程类 电信
作者
Sridhar Sripadmanabhan Indira,Chockalingam Aravind Vaithilingam,Kulasekharan Narasingamurthi,Ramsundar Sivasubramanian,Kok‐Keong Chong,R. Saidur
出处
期刊:Applied Energy [Elsevier]
卷期号:320: 119294-119294 被引量:21
标识
DOI:10.1016/j.apenergy.2022.119294
摘要

This article discusses the electrical and thermal performance of a hybrid concentrator photovoltaic thermal and solar thermoelectric generator (CPV/T-STEG) system using a compound parabolic concentrator (CPC) and a parabolic trough concentrator (PTC). For the first time, the idea of merging imaging and non-imaging concentrators for a CPV and TEG hybrid system is examined, providing an option to retrofit or remodel existing PTC-based CSP systems. The thermal resistance concept is applied to establish a steady-state mathematical model of the proposed hybrid CPV/T-STEG system. A Newton-Raphson iterative approach is employed to solve the mathematical model and compute the temperature in every layer of the hybrid system. After validation, the mathematical model is employed to evaluate the overall performance of the hybrid system. The modelling results revealed that the electrical and thermal output of the developed hybrid system were higher by 2 and 1.6 times, respectively, when compared with the prior parabolic trough-based hybrid CPV/T-STEG system described in the literature. The effects of ambient temperature, wind speed, flow rate, number of TEGs, and solar concentration ratio on the electrical and thermal performance were investigated. The optimal number of TEGs required for maximum electrical performance under different solar concentration ratios is also obtained. Finally, the hybrid system's exergy efficiency is investigated for various solar concentration ratios. The simulation results revealed that the increase in the Reynolds number from 100 to 2000 improves the net electrical and thermal efficiency by 10.21% and 5.7%, respectively. At a fixed solar concentration ratio (CCPC=4suns and WPTC=2WCPC), the electrical efficiency of TEG drops by 81.4%, but the thermal efficiency increases by 16.81%, provided that the number of TEGs is increased from 1 to 17. The highest exergy of the hybrid system is 8.36% when CCPC=2suns and WPTC=2WCPC. Due to the poor efficiency of commercial TEGs, the overall exergy efficiency of the hybrid system decreases with an increasing solar concentration ratio. In the proposed hybrid system, a fluid channel separates both the PV and TEG modules; hence the electrical conversion efficiencies of both modules are not closely related.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
2秒前
失眠的冬易完成签到 ,获得积分10
5秒前
威武的之桃完成签到 ,获得积分10
5秒前
科研通AI2S应助楼下太吵了采纳,获得10
6秒前
松柏完成签到 ,获得积分10
6秒前
兼听则明完成签到,获得积分10
6秒前
qqqqy完成签到 ,获得积分10
6秒前
量子星尘发布了新的文献求助10
9秒前
minuxSCI完成签到,获得积分10
9秒前
往返完成签到,获得积分10
11秒前
apollo3232完成签到 ,获得积分0
11秒前
ChatGPT发布了新的文献求助10
12秒前
13秒前
liufan完成签到 ,获得积分10
15秒前
18秒前
coasting完成签到,获得积分10
19秒前
大模型应助科研通管家采纳,获得10
19秒前
19秒前
风清扬发布了新的文献求助10
19秒前
橙子完成签到 ,获得积分10
22秒前
23秒前
量子星尘发布了新的文献求助10
23秒前
ChatGPT发布了新的文献求助10
24秒前
勤劳的颤完成签到 ,获得积分10
27秒前
why完成签到 ,获得积分10
28秒前
yurunxintian完成签到,获得积分10
29秒前
kk完成签到,获得积分10
29秒前
量子星尘发布了新的文献求助10
31秒前
da49完成签到,获得积分10
32秒前
活力的香芦完成签到,获得积分10
37秒前
gulin完成签到,获得积分10
37秒前
研友_VZGVzn完成签到,获得积分10
38秒前
40秒前
ChatGPT发布了新的文献求助10
41秒前
peng完成签到 ,获得积分10
41秒前
Tbin完成签到,获得积分10
41秒前
量子星尘发布了新的文献求助10
42秒前
36456657完成签到,获得积分0
43秒前
sincyking完成签到,获得积分10
43秒前
小药童完成签到,获得积分0
46秒前
高分求助中
2025-2031全球及中国金刚石触媒粉行业研究及十五五规划分析报告 12000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
The Cambridge History of China: Volume 4, Sui and T'ang China, 589–906 AD, Part Two 1000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1000
Russian Foreign Policy: Change and Continuity 800
Real World Research, 5th Edition 800
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5698471
求助须知:如何正确求助?哪些是违规求助? 5124482
关于积分的说明 15221625
捐赠科研通 4853493
什么是DOI,文献DOI怎么找? 2604113
邀请新用户注册赠送积分活动 1555692
关于科研通互助平台的介绍 1513960