Franek, Ondrej

Pedersen, Gert F.

English

Recently introduced wind turbine blade deflection sensing system using ultrawideband technology is described. Challenges of simulating microwave propagation along the blade using the finite-difference time-domain method are outlined. Two straightforward techniques that have been used to speed up the finite-difference time-domain (FDTD) simulation are presented: load balancing of parallel processes and the moving frame technique. In addition, a simple method to reduce the numerical dispersion error of the FDTD method is presented.</p

    Aalborg UniversitetComputational Aspects of Simulating a Wind Turbine Blade Deflection Sensing SystemPedersen, Gert F.; Franek, OndrejPublished in:2018 International Workshop on Computing, Electromagnetics, and Machine Intelligence (CEMi'18)DOI (link to publication from Publisher):10.1109/CEMI.2018.8610574Publication date:2019Document VersionAccepted author manuscript, peer reviewed versionLink to publication from Aalborg UniversityCitation for published version (APA):Pedersen, G. F., & Franek, O. (2019). Computational Aspects of Simulating a Wind Turbine Blade DeflectionSensing System. In L. Gurel (Ed.), 2018 International Workshop on Computing, Electromagnetics, and MachineIntelligence (CEMi'18) (pp. 41-42). [8610574] IEEE. https://doi.org/10.1109/CEMI.2018.8610574General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright ownersand it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.            ? Users may download and print one copy of any publication from the public portal for the purpose of private study or research.            ? You may not further distribute the material or use it for any profit-making activity or commercial gain            ? You may freely distribute the URL identifying the publication in the public portal ?Take down policyIf you believe that this document breaches copyright please contact us at vbn@aub.aau.dk providing details, and we will remove access tothe work immediately and investigate your claim.Downloaded from vbn.aau.dk on: November 24, 2020Computational Aspects of Simulating a WindTurbine Blade Deflection Sensing SystemGert Frølund Pedersen1 and Ondřej Franek11APMS Section, Department of Electronic Systems, Aalborg University, DK-9220 Aalborg Øst, Denmarkgfp@es.aau.dkAbstract— Recently introduced wind turbine blade deflectionsensing system using ultrawideband technology is described.Challenges of simulating microwave propagation along the bladeusing the finite-difference time-domain method are outlined. Twostraightforward techniques that have been used to speed upthe FDTD simulation are presented: load balancing of parallelprocesses and the moving frame technique. In addition, a simplemethod to reduce the numerical dispersion error of the FDTDmethod is presented.I. INTRODUCTIONWind energy is one of the solutions to reducing our CO2footprint, but the cost of generating electricity from wind isstill relatively high. One way how to reduce the cost is toinstall larger rotors with longer blades, but this comes withincreased risk of tower strike due to the blade flexibility,and therefore the turbine is not allowed to operate in thestrongest winds when most of the energy could be harvested.Our proposed solution is a blade deflection sensing system,which will provide early warning for possible tower strike andconsequently allow the turbine into higher loads.The deflection sensing system [1] consists of two antennasat the tip of the blade and two antennas at its root, and acable inside the blade that feeds the tip antennas. Bending ofthe blade is determined by triangulation based on the timeof arrival of an ultrawideband (UWB) pulse covering the 3–5GHz band launched by the tip antennas and received at the rootantennas (see Fig. 1). Unfortunately, the tip antenna must beplaced inside the blade due to aerodynamic noise and exposureto lighting, and the pulsed wave needs to traverse the fiberglassshell at very high angle of incidence and then propagate almostparallel to the blade surface. As a result, there will be manymultipath components in the received waveform and the designof the wireless link becomes extremely challenging.In order to predict the link budget, we have simulatedthe propagation in our in-house finite-difference time-domain(FDTD) code. We have shown that despite the challengesthe FDTD method is capable of delivering results that arein good agreement with measurements [2]. However, due tothe enormous size of the blade (58.7 m) and necessary spatialresolution (5 mm), each simulation of the blade took 17 hoursto finish. Moreover, the numerical dispersion of the Yee-FDTDscheme [3] caused substantial distortion of the received pulse.In this paper, we present the measures that have been takento reduce the computation time of the simulations and tominimize the error due to numerical dispersion.Fig. 1. Principle of the wind turbine blade deflection sensing system withdistance estimation using time of arrival on UWB wireless links.II. LOAD BALANCINGThe simulation of the blade required using the perfectlymatched layers (PML) as an outer boundary imitating openspace. The PML thickness was 50 cells due to the elongatedshape of the computational domain and grazing incidence ofthe propagating waves. Since our in-house FDTD code usesMPI library for deployment on parallel clusters, the domainmust be partitioned into regular segments. However, the cornersegments contained large portions of the PML layers wheremore computations need to be performed per FDTD cycle.The entire simulation was then slowed down because othersegments needed to wait in each time step for the corner“heavy” ones.The solution to this problem was to perform load balancingof the segments [4] using a very simple algorithm. The benefitwas 22 % shorter running time of the simulation, by changingonly the boundaries of the MPI segments in the code, withoutmodifying the algorithm of the method itself.III. MOVING FRAME FDTD METHODRunning times have been significantly reduced by imple-menting the moving frame FDTD technique [5]. Since allimportant information of the short UWB pulse is contained ina very small volume of space at each time instant (see Fig. 2),it is possible to reduce the computational burden by calculatingthe FDTD update equations only in a subdomain (frame) that ismoving along the length of the blade as time progresses. Fieldsahead of the frame do not have to be calculated because thepulse did not reach there yet. On the other hand, fields behindthe frame need not be calculated either because all scatteringfrom this area arrives after the important part of the pulse.The z-coordinate frame boundaries are calculated at eachtime instant t in the simulation byz1 = zTX − vgt (1)z2 = z1 + vgT + buffer (2)© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Fig. 2. Principle of the Moving Frame FDTD method. The relevant fields (yellow) are enclosed between the pulse front (red) and pulse back (blue) spheres.As a result, only the fields inside the moving frame (bold outline) need to be calculated.where vg is the group velocity of propagation in the z-direction along the FDTD grid (lower than speed of light dueto numerical dispersion), T is the time interval of interest in theoutput pulse, and zTX is the z-coordinate of the TX antenna.The buffer accounts for slower propagation when the pulsetraverses the fiberglass shell of the blade.The pulse obtained using the moving frame technique is inexcellent agreement with FDTD applied on the full domain,see Fig. 3. The running times have been reduced from theoriginal 17 hours to 1.5 hours on our parallel cluster with 288cores, which allows for much faster optimizations.IV. DISPERSION COMPENSATIONThe pulse waveform as seen in Fig. 3 is affected bynumerical dispersion inherent in the FDTD method. To obtainmore accurate results, a dispersion compensation [6] can beapplied to the output waveform EE(comp) = E · e j(k̃z−k)r (3)where r is the distance between TX and RX, k = ω/c is thefree space (ideal) wavenumber andk̃z =2∆zarcsin(∆zc∆tsinω∆t2)(4)is the dispersive wavenumber due to FDTD propagation alongthe z-coordinate of the grid. Comparison of the dispersioncompensated waveform with measured pulse on a real bladeis shown in Fig. 4.V. CONCLUSIONSFDTD Simulation of UWB propagation along large irregu-larly shaped dielectric bodies, such as a wind turbine blade,can be challenging in terms of computational resources andaccuracy. However, as we have shown, even by applyingrelatively simple techniques and modifications, the runningtimes can be reduced, sometimes quite dramatically, and moreaccurate results can be obtained by compensating for thenumerical dispersion error.ACKNOWLEDGMENTThis work was supported by the Innovation Fund Denmark(“iRotor” project) and the Danish e-Infrastructure Cooperation(DeIC).Fig. 3. Comparison between fields obtained by the original full domainFDTD (blue) and the Moving Frame FDTD (red dashed) methods.Fig. 4. Comparison between output signals simulated with dispersioncompensation (blue) and measured (red). The delay includes also the travelingtime in the cable.REFERENCES[1] S. Zhang, T. L. Jensen, O. Franek, P. C. Eggers, K. Olesen, C. Byskov,and G. F. Pedersen, “UWB wind turbine blade deflection sensing for windenergy cost reduction,” Sensors, vol. 15, no. 8, pp. 19 768–19 782, 2015.[2] O. Franek, S. Zhang, K. Olesen, P. C. Eggers, C. Byskov, and G. F.Pedersen, “Numerical modeling of ultrawideband propagation along awind turbine blade,” IEEE Transactions on Antennas and Propagation,In press.[3] A. Taflove and S. C. Hagness, Computational electrodynamics: TheFinite-Difference Time-Domain Method, 3rd ed. Boston: Artech house,2005.[4] O. Franek, “A simple method for static load balancing of parallelFDTD codes,” in 2016 International Conference on Electromagnetics inAdvanced Applications (ICEAA). IEEE, 2016, pp. 587–590.[5] ——, “Numerical modeling of a wind turbine blade deflection sensingsystem using the moving frame FDTD method,” in 2018 InternationalConference on Electromagnetics in Advanced Applications (ICEAA).IEEE, 2018.[6] O. Franek, S. Zhang, K. Olesen, P. C. F. Eggers, C. Byskov, andG. F. Pedersen, “Application of numerical dispersion compensation ofthe Yee-FDTD algorithm on elongated domains,” in 2017 InternationalConference on Electromagnetics in Advanced Applications (ICEAA).IEEE, 2017, pp. 1243–1246.

Computational Aspects of Simulating a Wind Turbine Blade Deflection Sensing System

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Computational Aspects of Simulating a Wind Turbine Blade Deflection Sensing System

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