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http://dx.doi.org/10.9728/dcs.2016.17.3.157

The Development of the Predict Model for Solar Power Generation based on Current Temperature Data in Restricted Circumstances  

Lee, Hyunjin (Dept. of Computer Science & Software, Korea Soongsil Cyber University)
Publication Information
Journal of Digital Contents Society / v.17, no.3, 2016 , pp. 157-164 More about this Journal
Abstract
Solar power generation influenced by the weather. Using the weather forecast information, it is possible to predict the short-term solar power generation in the future. However, in limited circumstances such as islands or mountains, it can not be use weather forecast information by the disconnection of the network, it is impossible to use solar power generation prediction model using weather forecast. Therefore, in this paper, we propose a system that can predict the short-term solar power generation by using the information that can be collected by the system itself. We developed a short-term prediction model using the prior information of temperature and power generation amount to improve the accuracy of the prediction. We showed the usefulness of proposed prediction model by applying to actual solar power generation data.
Keywords
Prediction of solar power generation; Data mining; Neural networks; Weather data;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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