Preliminary Analysis of Short-term Solar Irradiance Forecasting by using Total-sky Imager and Convolutional Neural Network

Anto Ryu, Masakazu Ito, Hideo Ishii, Yasuhiro Hayashi

研究成果: Conference contribution

9 被引用数 (Scopus)

抄録

The installation of photovoltaic system (PV) is increasing rapidly across the world. However, the fluctuation of PV output causes serious challenges in the power grid operation. Among the fluctuation, a quick part of fluctuation is mainly caused by the change of cloud coverage. A total-sky imager (TSI), measuring device to take sky and cloud, could be useful for short-term solar irradiance forecasting. In this paper, a convolutional neural network (CNN) is applied to forecasting model (called CNN model) to forecast 5-20 min ahead of global horizontal irradiance (GHI) using total-sky images and lagged GHI. To verify the effectiveness of CNN, three forecasting models are compared. They are the persistence model, the CNN model using only total-sky images, and the CNN model using both total-sky images and lagged GHI. From the computation, the proposed CNN model using both total-sky images and lagged GHI performs root-mean-square error (RMSE) of 49-177W/m2, 93-146W/m2, 71-118W/m2 in sunny day, partly cloudy day and overcast day, respectively. From these results, the proposed method is shown to be suitable for short-term solar irradiance forecasting.

本文言語English
ホスト出版物のタイトル2019 IEEE PES GTD Grand International Conference and Exposition Asia, GTD Asia 2019
出版社Institute of Electrical and Electronics Engineers Inc.
ページ627-631
ページ数5
ISBN(電子版)9781538674345
DOI
出版ステータスPublished - 2019 5 15
イベント2019 IEEE PES GTD Grand International Conference and Exposition Asia, GTD Asia 2019 - Bangkok, Thailand
継続期間: 2019 3 192019 3 23

出版物シリーズ

名前2019 IEEE PES GTD Grand International Conference and Exposition Asia, GTD Asia 2019

Conference

Conference2019 IEEE PES GTD Grand International Conference and Exposition Asia, GTD Asia 2019
CountryThailand
CityBangkok
Period19/3/1919/3/23

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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