Forecast of solar irradiance using recurrent neural networks combined with wavelet analysis

Cao, Shukun; Cao, Jinxin

doi:10.1016/j.applthermaleng.2004.06.017

Cited by 112 publications

(33 citation statements)

References 5 publications

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“…Equation (7.2) is expressing the standard autocorrelation problem, but this time the solutions are developed by AI techniques (Kemmoku et al 1999;Mihalakakou et al 2000;Cao and Cao 2005;Mellit et al 2006;Hocaoglu et al 2008;Cao and Lin 2008;.…”

Section: Artificial Intelligence Techniquesmentioning

confidence: 99%

Weather Modeling and Forecasting of PV Systems Operation

Paulescu¹,

Paulescu²,

Gravila³

et al. 2013

Green Energy and Technology

137

103

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Section: Artificial Intelligence Techniquesmentioning

confidence: 99%

Weather Modeling and Forecasting of PV Systems Operation

Paulescu¹,

Paulescu²,

Gravila³

et al. 2013

Green Energy and Technology

137

103

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“…Cao and Cao [104][105][106][107][108] they all combined wavelet with ANN. Other authors like [109][110][111][112][113][114][115][116][117][118][119][120][121][122][123] used other soft computing techniques like GA, fuzzy logic, Quantum based GA, adaptive neurofuzzy, etc.…”

Section: Hybrid Methodsmentioning

confidence: 99%

Solar Power Forecasting: A Review

K.¹,

Isha²

2016

IJCA

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The increasing demand for energy is one of the biggest reasons behind the integration of solar energy into the electric grids or networks. To ensure the efficient use of energy PV systems it becomes important to forecast information reliably. The accurate prediction of solar irradiance variation can enhance the quality of service. This integration of solar energy and accurate prediction can help in better planning and distribution of energy.Here in this paper, a deep review of methods which are used for solar irradiance forecasting is presented. These methods help in selecting the appropriate forecast technique according to the needs or requirements. This paper also presents the metrics that are used for evaluating the performance of a forecast model.

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“…In order to solve these problems, Wavelet Transform (WT) has been developed. WT is a kind of variable window technology, which uses a time interval to analyze the high frequency and the low frequency components of the signal [5], [6]. The data using WT can be decomposed into approximation and detail coefficients in a multi-scale, presenting then a more effective tool for non-stationary signal analysis than the FT.…”

Section: Introductionmentioning

confidence: 99%

Application of Wavelet Transform for Fault Diagnosis in Swash Plate Pump’s Control Unit Causing Pipes Flutter

Chikhalsouk¹,

Bhat²

2015

IJMMM

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Abstract-Vibration analysis is fundamental in enhancing condition monitoring and fault diagnostics of control unit in swash plate pumps. Several signal analysis methods are used to obtain useful information from vibration signatures. Presently, the most of these methods use spectral analysis based on Fourier Transform (FT). However, these methods exhibit some limitations; it is the case of transient signals when the irregularity is the pattern. In the present paper, we are interested to apply Discrete Wavelet Analysis (DWA) to the vibration signal analysis. The DWT is one of the most promising methods for signal processing; it is especially convenient for transient vibration measurements obtained from accelerometer sensors. The monitoring results indicate that the DWT can diagnose the abnormal change in the measured data.Index Terms-Vibration analysis, fault diagnosis, control unit, swash plate pumps, spectral analysis, wavelet transforms.

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Forecast of solar irradiance using recurrent neural networks combined with wavelet analysis

Cited by 112 publications

References 5 publications

Weather Modeling and Forecasting of PV Systems Operation

Weather Modeling and Forecasting of PV Systems Operation

Solar Power Forecasting: A Review

Application of Wavelet Transform for Fault Diagnosis in Swash Plate Pump’s Control Unit Causing Pipes Flutter

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