influence of raw data analysis for the use of neural networks for wind farm productivity prediction

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1 Citazione (Scopus)

Abstract

In the last decade wind energy had a strong growth because of cost effectiveness of the technology and the high remunerative of investments. The increase of wind power penetration in power grids, however, makes necessary the development of instruments for prediction of productivity of a wind farm. This paper presents a study dealing with the capability of neural network to forecast short term production of a wind farm by the correlation of wind and energy production data. Available measures of wind parameters were related to productivity data of a real wind farm. Also wind data not strictly related to the site have been used in order to assess their possible influence on the production. After a first step of data pre-processing a statistical analysis has been done. The model of input-output correlation is based on the use of artificial neural networks.
Lingua originaleEnglish
Stato di pubblicazionePublished - 2011

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Farms
Productivity
Neural networks
Wind power
Cost effectiveness
Statistical methods
Processing

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment

Cita questo

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title = "influence of raw data analysis for the use of neural networks for wind farm productivity prediction",
abstract = "In the last decade wind energy had a strong growth because of cost effectiveness of the technology and the high remunerative of investments. The increase of wind power penetration in power grids, however, makes necessary the development of instruments for prediction of productivity of a wind farm. This paper presents a study dealing with the capability of neural network to forecast short term production of a wind farm by the correlation of wind and energy production data. Available measures of wind parameters were related to productivity data of a real wind farm. Also wind data not strictly related to the site have been used in order to assess their possible influence on the production. After a first step of data pre-processing a statistical analysis has been done. The model of input-output correlation is based on the use of artificial neural networks.",
author = "Marco Beccali and Simona Culotta and Macaione",
year = "2011",
language = "English",

}

TY - CONF

T1 - influence of raw data analysis for the use of neural networks for wind farm productivity prediction

AU - Beccali, Marco

AU - Culotta, Simona

AU - Macaione, null

PY - 2011

Y1 - 2011

N2 - In the last decade wind energy had a strong growth because of cost effectiveness of the technology and the high remunerative of investments. The increase of wind power penetration in power grids, however, makes necessary the development of instruments for prediction of productivity of a wind farm. This paper presents a study dealing with the capability of neural network to forecast short term production of a wind farm by the correlation of wind and energy production data. Available measures of wind parameters were related to productivity data of a real wind farm. Also wind data not strictly related to the site have been used in order to assess their possible influence on the production. After a first step of data pre-processing a statistical analysis has been done. The model of input-output correlation is based on the use of artificial neural networks.

AB - In the last decade wind energy had a strong growth because of cost effectiveness of the technology and the high remunerative of investments. The increase of wind power penetration in power grids, however, makes necessary the development of instruments for prediction of productivity of a wind farm. This paper presents a study dealing with the capability of neural network to forecast short term production of a wind farm by the correlation of wind and energy production data. Available measures of wind parameters were related to productivity data of a real wind farm. Also wind data not strictly related to the site have been used in order to assess their possible influence on the production. After a first step of data pre-processing a statistical analysis has been done. The model of input-output correlation is based on the use of artificial neural networks.

UR - http://hdl.handle.net/10447/57753

M3 - Paper

ER -