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Short-term forecasting model for electric power production of small-hydro power plants

Title
Short-term forecasting model for electric power production of small-hydro power plants
Type
Article in International Scientific Journal
Year
2013
Authors
Ramirez Rosado, IJ
(Author)
Other
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Alfredo Fernandez Jimenez, LA
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
Journal
Title: Renewable EnergyImported from Authenticus Search for Journal Publications
Vol. 50
Pages: 387-394
ISSN: 0960-1481
Publisher: Elsevier
Other information
Authenticus ID: P-002-12Y
Abstract (EN): This paper presents an original short-term forecasting model for hourly average electric power production of small-hydro power plants (SHPPs). The model consists of three modules: the first one gives an estimation of the "daily average" power production; the second one provides the final forecast of the hourly average power production taking into account operation strategies of the SHPPs; and the third one allows a dynamic adjustment of the first module estimation by assimilating recent historical production data. The model uses, as inputs, forecasted precipitation values from Numerical Weather Prediction tools and past recorded values of hourly electric power production in the SHPPs. The structure of the model avoids crossed-influences between the adjustments of such model due to meteorological effects and those due to the operation strategies of the SHPPs. The forecast horizon of the proposed model is seven days. which allows the use of the final forecast of the power production in Power System operations, in electricity markets, and in maintenance scheduling of SHPPs. The model has been applied in the forecasting of the aggregated hourly average power production for a real-life set of 130 SHPPs in Portugal achieving satisfactory results, maintaining the forecasting errors delimited in a narrow band with low values.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 8
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