Presenter : Cheng-Han Tsai Authors : Adel Mellit , Alessandro Massi Pavan

Intelligent Database Systems Lab

國立雲林科技大學National Yunlin University of Science and Technology

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A 24-h forecast of solar irradiance using artificial neural network: Application for performance prediction of a

grid-connected PV plant at Trieste, Italy

Presenter : Cheng-Han Tsai 　Authors : Adel Mellit , Alessandro Massi Pavan

Solar Energy, 2010

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.

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Outlines Motivation Objectives Methodology Experiments Conclusions Comments

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Motivation· The previous approaches cannot forecast

several hours or average daily values of solar irradiance─ based on some meteorological parameters─ based on the past observed data─ hybrid

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Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Objectives· A simplified approach for forecasting 24-h

ahead of solar irradiance using a MLP is proposed

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Intelligent Database Systems Lab

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I. M.Methodology

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I. M.Methodology

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I. M.Experiments

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I. M.Experiments

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I. M.Experiments

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I. M.Experiments

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I. M.Experiments

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I. M.Experiments· November 23rd 2009–January 24th 2010 (9 h per day)

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I. M.Experiments

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Intelligent Database Systems Lab

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I. M.Conclusions· This architecture is suitable for forecasting of

solar irradiance at Trieste in Italy.

· This method can play a very important role for an efficient planning of the operation of renewable systems.

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Intelligent Database Systems Lab

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I. M.

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Comments· Advantages

─ This approach has many advantages with other existing methods

· Applications─ Forecast of solar irradiance