Evaluation of photovoltaic solar power using the different operating temperature models over a tropical region

被引:1
|
作者
Ojo, Olusola Samuel [1 ]
机构
[1] Fed Univ Technol Akure, Dept Phys, PMB 704, Akure, Ondo, Nigeria
关键词
Photovoltaic module; Operating temperature; Electrical efficiency; Solar power; Nigeria; PERFORMANCE;
D O I
10.1007/s12667-023-00604-0
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
This study aimed to propose a suitable photovoltaic operating temperature model for generating optimal solar power across tropical climate regions using Nigeria as a case study. Ten existing models were evaluated using air temperature, solar radiation, and wind speed data obtained from the National Aeronautics and Space Administration's Modern-Era Retrospective Analysis for Research and Applications, Version 2 archives over an 11-year period (2010-2020). The analyses revealed that the Risser-Fuentes model and Charles model produced the highest and lowest operating temperature values, respectively. The operating temperature values obtained from each of the models were then used in the PV energy model to generate solar power and evaluate its electrical efficiency. The results showed that the operating temperature value from the Charles model produced the highest solar power and maximum electrical efficiency across Nigeria's four climate regions, for both the seasonal and an annual timescales. The study concluded that the lower the operating temperature of the photovoltaic module, the greater the possibility of generating more solar power with greater electrical efficiency. Therefore, the study recommends the use of the Charles model for PV system size optimization, simulation, and design for solar power generation across all climate regions in Nigeria.
引用
收藏
页数:23
相关论文
共 50 条
  • [1] Modeling of the Photovoltaic Module Operating Temperature for Various Weather Conditions in the Tropical Region
    Diouf, Mame Cheikh
    Faye, Mactar
    Thiam, Ababacar
    Ndiaye, Alphousseyni
    Sambou, Vincent
    FDMP-FLUID DYNAMICS & MATERIALS PROCESSING, 2022, 18 (05): : 1275 - 1284
  • [2] Models to predict the operating temperature of different photovoltaic modules in outdoor conditions
    Mora Segado, Patricia
    Carretero, Jesus
    Sidrach-de-Cardona, Mariano
    PROGRESS IN PHOTOVOLTAICS, 2015, 23 (10): : 1267 - 1282
  • [3] Simulation and projection of photovoltaic energy potential over a tropical region using CMIP6 models
    Ojo, Olusola Samuel
    Adesemoye, Promise Dunsin
    JOURNAL OF ATMOSPHERIC AND SOLAR-TERRESTRIAL PHYSICS, 2024, 265
  • [4] Estimation of irradiance and temperature of solar photovoltaic system operating at maximum power point
    Owais, Raja
    Javed Iqbal, Sheikh
    International Journal of Ambient Energy, 2023, 44 (01): : 124 - 130
  • [5] Sensitivity analysis of solar irradiance estimates over a tropical region by cloud index models
    de Siqueira, Ricardo Almeida
    Goncalves, Andre Rodrigues
    Costa, Rodrigo Santos
    Martins, Fernando Ramos
    SOLAR ENERGY, 2025, 287
  • [6] Solar photovoltaic power prediction using different machine learning methods
    Zazoum, Bouchaib
    ENERGY REPORTS, 2022, 8 : 19 - 25
  • [7] Solar photovoltaic power prediction using different machine learning methods
    Zazoum, Bouchaib
    Energy Reports, 2022, 8 : 19 - 25
  • [8] Experimental investigation on the abasement of operating temperature in solar photovoltaic panel using PCM and aluminium
    Rajvikram, M.
    Leoponraj, S.
    Ramkumar, S.
    Akshaya, H.
    Dheeraj, A.
    SOLAR ENERGY, 2019, 188 : 327 - 338
  • [9] Comparison of Power Output Between Fixed and Perpendicular Solar Photovoltaic PV Panel in Tropical Climate Region
    Sukarno, Kartini
    Abd Hamie, Ag Sufiyan
    Jackson, Chang H. W.
    Pien, Chee Fuei
    Dayou, Jedol
    ADVANCED SCIENCE LETTERS, 2017, 23 (02) : 1259 - 1263
  • [10] Assessment of solar energy potential in China using an ensemble of photovoltaic power models
    Chen, Yuwen
    Yue, Xu
    Tian, Chenguang
    Letu, Husi
    Wang, Lunche
    Zhou, Hao
    Zhao, Yuan
    Fu, Weijie
    Zhao, Xu
    Peng, Daofu
    Zhang, Jia
    SCIENCE OF THE TOTAL ENVIRONMENT, 2023, 877