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http://dx.doi.org/10.7836/kses.2017.37.1.025

Prediction and Accuracy Analysis of Photovoltaic Module Temperature based on Predictive Models in Summer  

Lee, Yea-Ji (Department of Architectural Design and Engineering, Incheon National University)
Kim, Yong-Shik (Division of Architecture & Urban Planning, Incheon National University)
Publication Information
Journal of the Korean Solar Energy Society / v.37, no.1, 2017 , pp. 25-38 More about this Journal
Abstract
Climate change and environmental pollution are becoming serious due to the use of fossil energy. For this reason, renewable energy systems are increasing, especially photovoltaic systems being more popular. The photovoltaic system has characteristics that are affected by ambient weather conditions such as insolation, outside temperature, wind speed. Particularly, it has been confirmed that the performance of the photovoltaic system decreases as the module temperature increases. In order to grasp the influence of the module temperature in advance, several researchers have proposed the prediction models on the module temperature. In this paper, we predicted the module temperature using the aforementioned prediction model on the basis of the weather conditions in Incheon, South Korea during July and August. The influence of weather conditions (i.e. insolation, outside temperature, and wind speed) on the accuracy of the prediction models was also evaluated using the standard statistical metrics such as RMSE, MAD, and MAPE. The results show that the prediction accuracy is reduced by 3.9 times and 1.9 times as the insolation and outside temperature increased respectively. On the other hand, the accuracy increased by 6.3 times as the wind speed increased.
Keywords
Photovoltaic system; Module temperature; Prediction model; Weather conditions;
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