Analysis of the influencing factors of the dust on the surface of photovoltaic panels and its weakening law to solar radiation d A case study of Tianjin

被引:17
|
作者
Yao, Wanxiang [1 ,2 ]
Han, Xiao [3 ]
Huang, Yu [3 ]
Zheng, Zhimiao [4 ]
Wang, Yan [5 ]
Wang, Xiao [6 ]
机构
[1] Tianjin Chengjian Univ, Tianjin Key Lab Civil Struct Protect & Reinforcem, Tianjin 300384, Peoples R China
[2] Zhejiang Energy Grp R&D Inst Co Ltd, Key Lab Solar Energy Utilizat & Energy Saving Tec, Hangzhou 311121, Peoples R China
[3] Tianjin Chengjian Univ, Sch Energy & Safety Engn, Tianjin 300384, Peoples R China
[4] Beijing Univ Technol, Key Lab Green Built Environm & Energy Efficient T, Beijing 100124, Peoples R China
[5] Tianjin Chengjian Univ, Sch Architecture, Tianjin 300384, Peoples R China
[6] Tianjin Chengjian Univ, Sch Econ & Management, Tianjin 300384, Peoples R China
基金
中国国家自然科学基金;
关键词
Cleaning time; Dust density; PV efficiency; Solar radiation; Transmission; PV MODULES; EXPERIMENTAL VALIDATION; PERFORMANCE; DEPOSITION; ACCUMULATION; IMPACT; SYSTEM; TRANSMITTANCE; ORIENTATION; COVERS;
D O I
10.1016/j.energy.2022.124669
中图分类号
O414.1 [热力学];
学科分类号
摘要
With the intensification of energy crisis and environmental pollution, solar photovoltaic technology has been paid more and more attention by many countries. However, dust on the surface of the photovoltaic panels is one of the main factors affecting solar photovoltaic (PV). In this paper, multiple factors (pre-cipitation, wind speed, wind direction and inclination angle) were considered to analyze the effect of dust on the PV panels by weighing and transmittance determination in Tianjin, China. A test platform with 4 typical orientation and 7 inclination was built to measure the transmission of PV panels in the outdoor. The results showed that the southward PV panels were affected by wind velocity and direction more than others. Dust on southward PV panels increased rapidly at first, and then decreased under the influence of rainfall. Without rainfall, the dust on southward PV panels placed in 45 degrees for 30 days was 1.90% lower than that in the eastward, and 7.32% and 11.95% higher than those in the westward and northward, respectively. The functional relationship between dust density and dip angle was established by regression analysis, and the best cleaning time of PV panels is once a month except in rainy season. (c) 2022 Elsevier Ltd. All rights reserved.
引用
收藏
页数:9
相关论文
共 50 条
  • [21] Analysis of influencing factors and prediction of carbon emissions of typical urban agglomerations in China: a case study of Beijing-Tianjin-Hebei region
    Yuansheng Huang
    Jiajie Liu
    Mengshu Shi
    Environmental Science and Pollution Research, 2023, 30 : 52658 - 52678
  • [22] Evolution and analysis of urban resilience and its influencing factors: a case study of Jiangsu Province, China
    Xiaotong You
    Yanan Sun
    Jiawei Liu
    Natural Hazards, 2022, 113 : 1751 - 1782
  • [23] Analysis of Soybean Supply Fluctuations and Its Influencing Factors-A Case Study in Jilin Province
    Li, Chenxi
    Liu, Shuai
    Liu, Wenming
    PROCEEDINGS OF THE 2017 7TH INTERNATIONAL CONFERENCE ON EDUCATION, MANAGEMENT, COMPUTER AND SOCIETY (EMCS 2017), 2017, 61 : 275 - 280
  • [24] Evolution and analysis of urban resilience and its influencing factors: a case study of Jiangsu Province, China
    You, Xiaotong
    Sun, Yanan
    Liu, Jiawei
    NATURAL HAZARDS, 2022, 113 (03) : 1751 - 1782
  • [25] Analysis of influencing factors and prediction of carbon emissions of typical urban agglomerations in China: a case study of Beijing-Tianjin-Hebei region
    Huang, Yuansheng
    Liu, Jiajie
    Shi, Mengshu
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (18) : 52658 - 52678
  • [26] Investigating the nonlinear relationship between surface solar radiation and its influencing factors in North China Plain using interpretable machine learning
    Li, Zhigang
    Shi, Haoze
    Yang, Xin
    Tang, Hong
    Atmospheric Research, 2022, 280
  • [27] Investigating the nonlinear relationship between surface solar radiation and its influencing factors in North China Plain using interpretable machine learning
    Li, Zhigang
    Shi, Haoze
    Yang, Xin
    Tang, Hong
    ATMOSPHERIC RESEARCH, 2022, 280
  • [28] Analysis of the coupling characteristics of land transfer and carbon emissions and its influencing factors: A case study of China
    Zhang, Maomao
    Zhang, Ziyi
    Tong, Bin
    Ren, Bing
    Zhang, Lei
    Lin, Xuehan
    FRONTIERS IN ENVIRONMENTAL SCIENCE, 2023, 10
  • [29] PERFORMANCE ASSESSMENT AND THE ANALYSIS OF ITS INFLUENCING FACTORS IN ROMANIAN UNIVERSITIES BY USING MALMQUIST DEA: A CASE STUDY
    Olariu, Gabriela Vica
    Brad, Stelian
    PERFORMANCE MANAGEMENT OR MANAGEMENT PERFORMANCE?, 2018, : 7 - 13
  • [30] The evolution process of ecological vulnerability and its quantitative analysis of influencing factors: a case study of Longdong area
    Ma, Lixia
    Kang, Hou
    He, Dan
    Liu, Jiawei
    Tang, Haojie
    Wu, Siqi
    Li, Xuxiang
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (18) : 51464 - 51490