Mother wavelet selection in the discrete wavelet transform for condition monitoring of wind turbine drivetrain bearings

Wind Energy ◽  
2019 ◽  
Vol 22 (11) ◽  
pp. 1581-1592 ◽  
Author(s):  
Daniel Strömbergsson ◽  
Pär Marklund ◽  
Kim Berglund ◽  
Juhamatti Saari ◽  
Allan Thomson
Keyword(s):  
Wavelet Transform ◽  
Wind Turbine ◽  
Discrete Wavelet Transform ◽  
Condition Monitoring ◽  
Discrete Wavelet ◽  
Mother Wavelet ◽  
Wavelet Selection

scholarly journals Pulmonary crackle characterization: approaches in the use of discrete wavelet transform regarding border effect, mother-wavelet selection, and subband reduction

2015 ◽  
Vol 31 (2) ◽  
pp. 148-159 ◽  
Author(s):  
Verônica Isabela Quandt ◽  
Edras Reily Pacola ◽  
Sérgio Francisco Pichorim ◽  
Humberto Remigio Gamba ◽  
Miguel Antônio Sovierzoski
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
Border Effect ◽  
Mother Wavelet ◽  
Wavelet Selection

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
Keyword(s):  
Wavelet Transform ◽  
Wind Turbine ◽  
Discrete Wavelet Transform ◽  
Real Time ◽  
Power Output ◽  
Discrete Wavelet ◽  
Smoothing Technique ◽  
The Real ◽  
Power Smoothing ◽  
Li Ion

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.

Sign in / Sign up

Export Citation Format

Share Document