2015
DOI: 10.1007/s00521-015-1921-0
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Estimating the energy production of the wind turbine using artificial neural network

Abstract: Due to fluctuating weather conditions, estimating wind energy potential is still a significant problem. Artificial neural networks (ANNs) have been commonly used in short-term and just-in-time modeling of wind power generation systems based on main weather parameters such as wind speed, temperature, and humidity. Two different datasets called hourly main weather data (MWD) and daily sub-data (DSD) are used to estimate a wind turbine power generation in this study. MWD are based on historically observed wind sp… Show more

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Cited by 27 publications
(12 citation statements)
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“…Those indicate the degree of correlation between measured and estimated values. Thus, the reliability of the models could be tested because higher reliability means more accurate P orc estimation [44][45][46].…”
Section: Evaluation Criteriamentioning
confidence: 99%
“…Those indicate the degree of correlation between measured and estimated values. Thus, the reliability of the models could be tested because higher reliability means more accurate P orc estimation [44][45][46].…”
Section: Evaluation Criteriamentioning
confidence: 99%
“…A layered ANN structure, called multilayer perceptron (MLP), is one of the most widespread ANN methods especially in structural identification (He and Yan 2007) (see Figure 1(c)). In general, a conventional ANN has three layers which are input layer, hidden layer and output layer (Mert et al 2015). ANNs can be categorized by their network topology such as feed forward and feedback or by their learning algorithms such as supervised learning and unsupervised learning (Azimzadegan et al 2012).…”
Section: Artificial Neural Network (Ann)mentioning
confidence: 99%
“…Whether to consider the time factor or not, the use of static neural network can be found widely in various applications (e.g. [16][17][18][19][20]). Relatively, the time factor is explicit represented in the dynamic neural network model, by using feedback loop to cause time delays.…”
Section: Structure Of Neural Network Modelsmentioning
confidence: 99%