scholarly journals Discrete Wavelet Transform for the Real-Time Smoothing of Wind Turbine Power Using Li-Ion Batteries

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2184
Author(s):  
Andrea Mannelli ◽  
Francesco Papi ◽  
George Pechlivanoglou ◽  
Giovanni Ferrara ◽  
Alessandro Bianchini

Energy Storage Systems (EES) are key to further increase the penetration in energy grids of intermittent renewable energy sources, such as wind, by smoothing out power fluctuations. In order this to be economically feasible; however, the ESS need to be sized correctly and managed efficiently. In the study, the use of discrete wavelet transform (Daubechies Db4) to decompose the power output of utility-scale wind turbines into high and low-frequency components, with the objective of smoothing wind turbine power output, is discussed and applied to four-year Supervisory Control And Data Acquisition (SCADA) real data from multi-MW, on-shore wind turbines provided by the industrial partner. Two main research requests were tackled: first, the effectiveness of the discrete wavelet transform for the correct sizing and management of the battery (Li-Ion type) storage was assessed in comparison to more traditional approaches such as a simple moving average and a direct use of the battery in response to excessive power fluctuations. The performance of different storage designs was compared, in terms of abatement of ramp rate violations, depending on the power smoothing technique applied. Results show that the wavelet transform leads to a more efficient battery use, characterized by lower variation of the averaged state-of-charge, and in turn to the need for a lower battery capacity, which can be translated into a cost reduction (up to −28%). The second research objective was to prove that the wavelet-based power smoothing technique has superior performance for the real-time control of a wind park. To this end, a simple procedure is proposed to generate a suitable moving window centered on the actual sample in which the wavelet transform can be applied. The power-smoothing performance of the method was tested on the same time series data, showing again that the discrete wavelet transform represents a superior solution in comparison to conventional approaches.

Author(s):  
Mohammad Asadi ◽  
Mehrshad Noori Harikandeh ◽  
Mohammadreza Hamzenia

Lack of power quality imposes many costs on large and small consumers every year. Therefore, considering the importance of power quality in today's industries, this article examines the issue of detection and location of various power quality issues. DWT discrete wavelet transform is investigated in this paper. The signals under the perturbations are written to the field and the start and end times of the perturbation are obtained and compared with the real time, and the accuracy of the measurements is confirmed by repetitions.


2009 ◽  
Vol 18 (08) ◽  
pp. 1505-1516
Author(s):  
XIN ZHENG ◽  
XIAODONG WANG ◽  
HAIFENG CUI ◽  
TONG RUAN

The real-time rendering of high-quality, non-uniform scenes based on viewpoint has always been one of the most difficult problems in the CG area. In this paper, we propose one efficient algorithm to solve this problem with the help of merging texture synthesis and discrete wavelet transform (DWT) techniques. Using a single normal-sized image input, we can efficiently obtain texture sizes with different resolutions and update these in real-time rendering with the help of DWT. The results of our experiments prove that our algorithm can smoothly and efficiently render the non-uniform scenes based on viewpoint.


Wind Energy ◽  
2019 ◽  
Vol 22 (11) ◽  
pp. 1581-1592 ◽  
Author(s):  
Daniel Strömbergsson ◽  
Pär Marklund ◽  
Kim Berglund ◽  
Juhamatti Saari ◽  
Allan Thomson

2016 ◽  
Vol 14 (4) ◽  
pp. 1662-1668 ◽  
Author(s):  
Ernano Arrais Junior ◽  
Ricardo Alexandro de Medeiros Valentim ◽  
Glaucio Bezerra Brandao

2013 ◽  
Vol 284-287 ◽  
pp. 2402-2406 ◽  
Author(s):  
Rong Choi Lee ◽  
King Chu Hung ◽  
Huan Sheng Wang

This thesis is to approach license-plate recognition using 2D Haar Discrete Wavelet Transform (HDWT) and artificial neural network. This thesis consists of three main parts. The first part is to locate and extract the license-plate. The second part is to train the license-plate. The third part is to real time scan recognition. We select only after the second 2D Haar Discrete Wavelet Transform the image of low-frequency part, image pixels into one-sixteen, thus, reducing the image pixels and can increase rapid implementation of recognition and the computer memory. This method is to scan for car license plate recognition, without make recognition of the individual characters. The experimental result can be high recognition rate.


Biometrics ◽  
2017 ◽  
pp. 761-777
Author(s):  
Di Zhao

Mobile GPU computing, or System on Chip with embedded GPU (SoC GPU), becomes in great demand recently. Since these SoCs are designed for mobile devices with real-time applications such as image processing and video processing, high-efficient implementations of wavelet transform are essential for these chips. In this paper, the author develops two SoC GPU based DWT: signal based parallelization for discrete wavelet transform (sDWT) and coefficient based parallelization for discrete wavelet transform (cDWT), and the author evaluates the performance of three-dimensional wavelet transform on SoC GPU Tegra K1. Computational results show that, SoC GPU based DWT is significantly faster than SoC CPU based DWT. Computational results also show that, sDWT can generally satisfy the requirement of real-time processing (30 frames per second) with the image sizes of 352×288, 480×320, 720×480 and 1280×720, while cDWT can only obtain read-time processing with small image sizes of 352×288 and 480×320.


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