Details

Autor(en) / Beteiligte

• Gholami, Aslan
• Ameri, Mohammad
• Zandi, Majid
• Gavagsaz Ghoachani, Roghayeh
• Jafarzadegan Gerashi, Saeed
• Kazem, Hussein A
• Al-Waeli, Ali H.A.

Titel

Impact of harsh weather conditions on solar photovoltaic cell temperature: Experimental analysis and thermal-optical modeling

Ist Teil von

• Solar energy, 2023-03, Vol.252, p.176-194

Ort / Verlag

Elsevier Ltd

Erscheinungsjahr

2023

Quelle

Elsevier ScienceDirect Journals

Beschreibungen/Notizen

• [Display omitted] •Experiential investigation of parameters affecting a photovoltaic cell temperature.•Provide semi-empirical correlation forms to predict cell temperature.•Simulating detailed temperature distributions of a photovoltaic panel.•Provide a state-of-the-art reference for modeling under any varying conditions.•Increase precision and reduce computational costs for predicting cell temperature. A photovoltaic panel cell temperature extremely affects its output, while is extensively affected by the variation in the environmental conditions. The current study investigated the main parameters affecting these regards and defines their independent and simultaneous impacts. It was shown that cell temperature depends directly on irradiation and ambient temperature, as well as inversely on humidity, wind speed, and the amount of accumulated dust on the surface of a panel with respectively standardized Beta coefficients of 0.541, 0.645, −0.035, −0.055 and −0.068. Based on the experimental and analytical analysis, five semi-empirical correlation forms were proposed to predict the cell temperature of a photovoltaic system with coefficients of determination of 0.728, 0.970, 0.972, 0.973, and 0.974. The detailed temperature distributions of a photovoltaic panel were also simulated by thermal-optical modeling under several harsh environmental conditions. Comparing the simulation results, correlation predictions, and experimental measurements confirmed complete consistency. Moreover, it was shown that considering the prediction precision, simplicity, and computational cost, the proposed correlation forms should be preferred. However, the thermal-optical modeling could predict the temperature distribution and provide more details. The proposed modified semi-empirical correlation forms in the current study can be easily coupled to other models to add precision and accuracy to the behavior prediction of a photovoltaic system under harsh weather conditions.