Presentation 2013-12-19
Uncertainty Assessment of Solar Radiation Forecasting under Smart Grid Environment
Masato TAKAHASIHI, Hiroyuki MORI,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) This paper proposes a kernel machine method for forecast solar radiation prediction with Gaussian Processes. Recently, renewable energy such as PV systems, wind power generation, etc. is popular in the world. Renewable energy plays an important role to suppress the CO_2 emissions. However, it is difficult to introduce renewable energy into smart grids because renewable energy brings about a large amount of the uncertainties to smart grids operation and planning so that higher accurate model is needed for the forecasting methods. This paper focuses on solar radiation forecasting in PV systems. The proposed method makes use of the hierarchical Bayesian model that expresses the distribution of the predicted value called error bars. The proposed method is successfully applied to real weather data.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Solar Radiation Forecasting / Kernel Machine / Gaussian Processes / Error Bar
Paper # SSS2013-28
Date of Issue

Conference Information
Committee SSS
Conference Date 2013/12/12(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Vice Chair

Paper Information
Registration To Safety (SSS)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Uncertainty Assessment of Solar Radiation Forecasting under Smart Grid Environment
Sub Title (in English)
Keyword(1) Solar Radiation Forecasting
Keyword(2) Kernel Machine
Keyword(3) Gaussian Processes
Keyword(4) Error Bar
1st Author's Name Masato TAKAHASIHI
1st Author's Affiliation Dept. of Electronics and Bioinformatics, Faculty of Science and Technology, Meiji University()
2nd Author's Name Hiroyuki MORI
2nd Author's Affiliation Dept. of Network Design, Faculty of Interdisciplinary Mathematical, Meiji University
Date 2013-12-19
Paper # SSS2013-28
Volume (vol) vol.113
Number (no) 362
Page pp.pp.-
#Pages 4
Date of Issue