多变天气条件下三种光伏电池板特性的高效建模与实验验证

IF 1.204 Q3 Energy
A. Hali, Y. Khlifi
{"title":"多变天气条件下三种光伏电池板特性的高效建模与实验验证","authors":"A. Hali, Y. Khlifi","doi":"10.3103/s0003701x23601631","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>This paper presents a validation of a proposal combined analytical and numerical approach applied to a single diode model of photovoltaic (PV) module for extracting its five PV parameters: shunt resistance, series resistance, diode ideality factor, photo-generated current and saturation current. This method is tested using data provided by manufacturer’s datasheets for three PV panels technologies: multicrystalline Kyocera (KC175GHT-2), monocrystalline Silicon Shell (SQ-150PC) and heterojunction with amorphous silicon “intrinsic thin-layer” “HIT-240HDE4” under variable environmental conditions. The simulation results in MATLAB environment show a good agreement between simulated and experimental power-voltage and current-voltage characteristics for different irradiation levels and temperature values. This accuracy of the proposed method has been confirmed by lowest root mean square error (RMSE) whatever the weather conditions compared to recent conventional approaches reported in the literature. Furthermore, this new approach is tested experimentally on three types of photovoltaic modules’ data provided by “NREL”: The National Renewable Energy Laboratory, USA. An accurate knowledge of photovoltaic panel parameters from measurement data is essential for solar panels quality control, design and estimating their performance. Indeed, the photovoltaic panel is prone to degrading over time owing to aging and weather exposure. Therefore, predicting these performance degradations is key to avoid their negative impacts on PV production. For this purpose, this work presents a fast, simple, and precise approach of PV parameters extraction to obtain an exact model which more accurately emulates the photovoltaic modules characteristics under a large interval of temperature and irradiation levels, and valid for different PV technologies. Also, from the performance comparison of these three PV panel technologies, we have concluded that the monocrystalline module shows the best performance on the Cocoa, Florida (subtropical climate) with an average performance ratio of 100%.</p>","PeriodicalId":475,"journal":{"name":"Applied Solar Energy","volume":null,"pages":null},"PeriodicalIF":1.2040,"publicationDate":"2024-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Efficient Modeling of Three Types Photovoltaic Panels Characteristics with Experimental Validation under Variable Weather Conditions\",\"authors\":\"A. Hali, Y. Khlifi\",\"doi\":\"10.3103/s0003701x23601631\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3 data-test=\\\"abstract-sub-heading\\\">Abstract</h3><p>This paper presents a validation of a proposal combined analytical and numerical approach applied to a single diode model of photovoltaic (PV) module for extracting its five PV parameters: shunt resistance, series resistance, diode ideality factor, photo-generated current and saturation current. This method is tested using data provided by manufacturer’s datasheets for three PV panels technologies: multicrystalline Kyocera (KC175GHT-2), monocrystalline Silicon Shell (SQ-150PC) and heterojunction with amorphous silicon “intrinsic thin-layer” “HIT-240HDE4” under variable environmental conditions. The simulation results in MATLAB environment show a good agreement between simulated and experimental power-voltage and current-voltage characteristics for different irradiation levels and temperature values. This accuracy of the proposed method has been confirmed by lowest root mean square error (RMSE) whatever the weather conditions compared to recent conventional approaches reported in the literature. Furthermore, this new approach is tested experimentally on three types of photovoltaic modules’ data provided by “NREL”: The National Renewable Energy Laboratory, USA. An accurate knowledge of photovoltaic panel parameters from measurement data is essential for solar panels quality control, design and estimating their performance. Indeed, the photovoltaic panel is prone to degrading over time owing to aging and weather exposure. Therefore, predicting these performance degradations is key to avoid their negative impacts on PV production. For this purpose, this work presents a fast, simple, and precise approach of PV parameters extraction to obtain an exact model which more accurately emulates the photovoltaic modules characteristics under a large interval of temperature and irradiation levels, and valid for different PV technologies. Also, from the performance comparison of these three PV panel technologies, we have concluded that the monocrystalline module shows the best performance on the Cocoa, Florida (subtropical climate) with an average performance ratio of 100%.</p>\",\"PeriodicalId\":475,\"journal\":{\"name\":\"Applied Solar Energy\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.2040,\"publicationDate\":\"2024-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Solar Energy\",\"FirstCategoryId\":\"1\",\"ListUrlMain\":\"https://doi.org/10.3103/s0003701x23601631\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Energy\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Solar Energy","FirstCategoryId":"1","ListUrlMain":"https://doi.org/10.3103/s0003701x23601631","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Energy","Score":null,"Total":0}
引用次数: 0

摘要

摘要 本文验证了一种结合分析和数值方法的建议,该方法适用于光伏(PV)模块的单二极管模型,用于提取其五个光伏参数:并联电阻、串联电阻、二极管表意系数、光生成电流和饱和电流。该方法使用制造商提供的数据表对三种光伏电池板技术进行了测试:多晶京瓷(KC175GHT-2)、单晶硅壳(SQ-150PC)和非晶硅 "本征薄层 "异质结 "HIT-240HDE4"。MATLAB 环境下的模拟结果表明,在不同的辐照水平和温度值下,模拟和实验的功率-电压和电流-电压特性非常吻合。与文献中报道的最新传统方法相比,该方法在任何天气条件下的均方根误差(RMSE)都最小,从而证实了所提出方法的准确性。此外,这种新方法还在 "NREL "提供的三种光伏组件数据上进行了实验测试:美国国家可再生能源实验室。从测量数据中准确了解光伏电池板参数对于太阳能电池板的质量控制、设计和性能评估至关重要。事实上,由于老化和天气暴露,光伏板很容易随着时间的推移而退化。因此,预测这些性能退化是避免其对光伏生产产生负面影响的关键。为此,本研究提出了一种快速、简单、精确的光伏参数提取方法,以获得一个精确模型,该模型能更准确地模拟光伏组件在大范围温度和辐照水平下的特性,并适用于不同的光伏技术。此外,通过对这三种光伏电池板技术的性能比较,我们得出结论,单晶硅组件在佛罗里达州可可市(亚热带气候)的表现最佳,平均性能比达到 100%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Efficient Modeling of Three Types Photovoltaic Panels Characteristics with Experimental Validation under Variable Weather Conditions

Efficient Modeling of Three Types Photovoltaic Panels Characteristics with Experimental Validation under Variable Weather Conditions

Abstract

This paper presents a validation of a proposal combined analytical and numerical approach applied to a single diode model of photovoltaic (PV) module for extracting its five PV parameters: shunt resistance, series resistance, diode ideality factor, photo-generated current and saturation current. This method is tested using data provided by manufacturer’s datasheets for three PV panels technologies: multicrystalline Kyocera (KC175GHT-2), monocrystalline Silicon Shell (SQ-150PC) and heterojunction with amorphous silicon “intrinsic thin-layer” “HIT-240HDE4” under variable environmental conditions. The simulation results in MATLAB environment show a good agreement between simulated and experimental power-voltage and current-voltage characteristics for different irradiation levels and temperature values. This accuracy of the proposed method has been confirmed by lowest root mean square error (RMSE) whatever the weather conditions compared to recent conventional approaches reported in the literature. Furthermore, this new approach is tested experimentally on three types of photovoltaic modules’ data provided by “NREL”: The National Renewable Energy Laboratory, USA. An accurate knowledge of photovoltaic panel parameters from measurement data is essential for solar panels quality control, design and estimating their performance. Indeed, the photovoltaic panel is prone to degrading over time owing to aging and weather exposure. Therefore, predicting these performance degradations is key to avoid their negative impacts on PV production. For this purpose, this work presents a fast, simple, and precise approach of PV parameters extraction to obtain an exact model which more accurately emulates the photovoltaic modules characteristics under a large interval of temperature and irradiation levels, and valid for different PV technologies. Also, from the performance comparison of these three PV panel technologies, we have concluded that the monocrystalline module shows the best performance on the Cocoa, Florida (subtropical climate) with an average performance ratio of 100%.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Applied Solar Energy
Applied Solar Energy Energy-Renewable Energy, Sustainability and the Environment
CiteScore
2.50
自引率
0.00%
发文量
0
期刊介绍: Applied Solar Energy  is an international peer reviewed journal covers various topics of research and development studies on solar energy conversion and use: photovoltaics, thermophotovoltaics, water heaters, passive solar heating systems, drying of agricultural production, water desalination, solar radiation condensers, operation of Big Solar Oven, combined use of solar energy and traditional energy sources, new semiconductors for solar cells and thermophotovoltaic system photocells, engines for autonomous solar stations.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信