Applying Artificial Intelligence in Forecasting the Output of Industrial Solar Power Plant in Vietnam

Quang, Ninh Nguyen and Duy, Linh Bui and Van, Binh Doan and Dinh, Quang Nguyen (2021) Applying Artificial Intelligence in Forecasting the Output of Industrial Solar Power Plant in Vietnam. EAI Endorsed Transactions on Energy Web. e29. ISSN 2032-944X

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Abstract

This paper uses recurrent neural network (Long Short – Term Memory - LSTM network) to build a model to forecast short-term generation capacity of Phong Dien solar power plant, (48 MWp – 35 MWAC) located in Thua Thien Hue Province, Viet Nam, with input factors including meteorological parameters. The authors conducted experiments to find the optimal structure of the model corresponding to the conditions of the plant and the data collection. Through this model, meteorological forecast data sets from commercial suppliers were used to forecast the plant's output power. The comments about the result as well as the further study direction are analysed and suggested.

Item Type: Article
Uncontrolled Keywords: Long Short – Term Memory, Industrial PV power plant, Forecasting PV power, Artificial Intelligence
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
T Technology > T Technology (General)
Depositing User: EAI Editor IV
Date Deposited: 20 Jul 2021 09:51
Last Modified: 20 Jul 2021 09:51
URI: https://eprints.eudl.eu/id/eprint/4892

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