This paper describes variable speed wind turbine (Types 3 and 4, IEC 61400–27-1) simulations based on an open-source solution to be applied to Bachelor and Master Degrees. It is an attempt to improve the education quality of such sustainable energy by giving an open-source experimental environment for both undergraduate and graduate students. Indeed, among the renewable sources, wind energy is currently becoming essential in most power systems. The simulations include both one–mass and two–mass mechanical models, as well as pitch angle control. A general overview of the structure, control, and operation of the variable speed wind turbine is provided by these easy-to-use interactive virtual experiments. In addition, a comparison between commercial and open-source software packages is described and discussed in detail. Examples and extensive results are also included in the paper. The models are available in Scilab-Xcos file exchange for power system education and researcher communities.
Fernández-GuillamónAVillena-LapazJVigueras-RodríguezA, et al.
An adaptive frequency strategy for variable speed wind turbines: application to high wind integration into power systems. Energies2018;
11: 1436.
2.
Fernández-GuillamónADasKCutululisNA, et al.
Offshore wind power integration into future power systems: overview and trends. J Marine Sci Eng2019;
7: 399.
3.
FragkosPParoussosL.Employment creation in EU related to renewables expansion. Appl Energy2018;
230: 935–945.
4.
KaldellisJKZafirakisD.The wind energy (r) evolution: a short review of a long history. Renew Energy2011;
36: 1887–1901.
5.
SwiftATegenSAckerT, et al.
Graduate and undergraduate university programs in wind energy in the United States. Wind Eng2019;
43: 35–46.
6.
DuranMBarreroFGonzalez-PrietoI, et al. A scientific approach in wind energy courses for electrical engineers. In: Technologies Applied to Electronics Teaching (TAEE). Piscataway: IEEE, 2016, pp. 1–6.
7.
SooriyaarachchiTMTsaiITEl KhatibS, et al.
Job creation potentials and skill requirements in, PV, CSP, wind, water-to-energy and energy efficiency value chains. Renew Sustain Energy Rev2015;
52: 653–668.
CameronLVan Der ZwaanB.Employment factors for wind and solar energy technologies: a literature review. Renew Sustain Energy Rev2015;
45: 160–172.
10.
CedazoRLopezDSanchezFM, et al.
Ciclope: Foss for developing and managing educational web laboratories. IEEE Trans Educ2007;
50: 352–359.
11.
ArribasJRVeganzonesCBlazquezF, et al.
Computer-based simulation and scaled laboratory bench system for the teaching and training of engineers on the control of doubly fed induction wind generators. IEEE Trans Power Syst2011;
26: 1534–1543.
12.
DuranMJBarreroFGonzález-PrietoI, et al. A scientific approach in wind energy courses for electrical engineers. In: 2016 Technologies Applied to Electronics Teaching (TAEE). Seville, Spain, 22–24 June 2016. pp. 1–6. IEEE.
13.
BentounsiADjeghloudHBenallaH, et al.
Computer-aided teaching using matlab/simulink for enhancing an IM course with laboratory tests. IEEE Trans Educ2011;
54: 479–491.
14.
TortoreliMDChatzarakisGEVoudoukisNF, et al.
Teaching fundamentals of photovoltaic array performance with simulation tools. Int J Electr Eng Educ2017;
54: 82–94.
15.
MoeiniAKamwaIBrunelleP, et al. Open data IEEE test systems implemented in SimPowerSystems for education and research in power grid dynamics and control. In: 2015 50th International Universities Power Engineering Conference (UPEC). Piscataway: IEEE, 2015, pp. 1–6
16.
DasKHansenADSørensenPE.Understanding IEC standard wind turbine models using SimPowerSystems. Wind Eng2016;
40: 212–227.
17.
ColeSBelmansR.MatDyn, a new matlab-based toolbox for power system dynamic simulation. IEEE Trans Power Syst2011;
26: 1129–1136.
18.
MilanoFVanfrettiL. State of the art and future of OSS for power systems. In: 2009 IEEE Power Energy Society General Meeting. Piscataway: IEEE, 2009, pp. 1–7.
19.
HmJH. The emergence of free and open–source software on campuses in Taiwan. In: Proceedings of the 2012 IEEE Global Humanitarian Technology Conference. Washington: IEEE Computer Society. ISBN 978-0-7695-4849-4, 2012, pp. 403–407.
20.
NehraVTyagiA.Free open source software in electronics engineering education: a survey. Int J Modern Educ Comput Sci2014;
6: 15–25.
21.
SeixasMMelícioRMendesVMF.Simulation by discrete mass modeling of offshore wind turbine system with dc link. Int J Marine Energy2016;
14: 80–100.
22.
EliasM.Impact of the bologna process on Spanish studentsprocess 2016.0. Int J Iberian Stud2010;
23: 53–62.
23.
HarmsenR.Future scenarios for the European higher education area: Exploring the possibilities of ‘Experimentalist governanceta Cham: Springer International Publishing. ISBN 978-3-319-20877-0, 2015, pp. 785–803.
24.
NjiriJGSöffkerD.State-of-the-art in wind turbine control: trends and challenges. Renew Sustain Energy Rev2016;
60: 377–393.
25.
SharmaNGobbertMK. A comparative evaluation of matlab, octave, freemat, and scilab for research and teaching. UMBC Faculty Collection2010. Technical Report, available at: https://userpages.umbc.edu/∼gobbert/papers/SharmaGobbertTR2010.pdf
26.
VijayalakshmiSAnuradhaCGanapathyV, et al. l.
Direct driven wind energy conversion system connected to load using variable frequency transformer. Int J Electr Eng Educ. Epub ahead of print2019. DOI: 10.1177/0020720919829011.
27.
KouroussisGFekihLBContiC. Easymod: A matlab/scilab toolbox for teaching modal analysis. In: 19th International Congress on Sound and Vibration (ICSV19), Vilnius, Lithuania. 8–12 July 2012.
28.
GlavelisTPloskasNSamarasN.A computational evaluation of some free mathematical software for scientific computing. J Comput Sci2010;
1: 150–158.
29.
RubtsovaAKorolevV. Scilab creating graphical applications. In: Abstracts of XXIII international scientific and practical conference of young scientists and student, Ukraine, vol. 2, p. 292. National University of Pharmacy.
30.
AriantoSYunaningsihRYAstutiET, et al. Development of single cell lithium ion battery model using Scilab/Xcos. In: AIP Conference Proceedings. Melville: AIP Publishing, vol. 1711, p. 060007.
31.
TonaP. Teaching process control with Scilab and Scicos. In: 2006 American Control Conference. Minneapolis, MN, USA, 2006, p. 6. IEEE.
32.
QinYKorkaliMTopP, et al. A JModelica.org library for power grid dynamic simulation with wind turbine control. In: IEEE Power Energy Society General Meeting (PESGM). Piscataway: IEEE, 2019, pp. 1–5.
33.
KanojBSanuMARajuAB. Steady state analysis of autonomous wind energy conversion system for irrigation purpose employing induction machines using python – a free and open source software. In: 2013 IEEE Global Humanitarian Technology Conference: South Asia Satellite (GHTC-SAS). Piscataway: IEEE, 2013, pp. 292–297.
34.
MillerNWSanchez-GascaJJPriceWW, et al. Dynamic modeling of ge 1.5 and 3.6 mw wind turbine-generators for stability simulations. In: Power engineering society general meeting. Piscataway: IEEE, 2003, vol. 3, pp. 1977–1983.
35.
UllahNRThiringerTKarlssonD.Temporary primary frequency control support by variable speed wind turbines—potential and applications. IEEE Trans Power Syst2008;
23: 601–612.
36.
Villena-RuizRJiménez-BuendíaFHonrubia-EscribanoA, et al.
Compliance of a generic type 3 WT model with the Spanish grid code. Energies2019;
12: 1631.
37.
Molina-GarcíaAFernández-GuillamónAGómez-LázaroE, et al.
Vertical wind profile characterization and identification of patterns based on a shape clustering algorithm. IEEE Access2019;
7: 30890–30904.
38.
RaghebMRaghebAM. Wind turbines theory-the betz equation and optimal rotor tip speed ratio. In: Fundamental and advanced topics in wind power. London: IntechOpen, 2011.
39.
AtaRKoçyigitY.An adaptive neuro-fuzzy inference system approach for prediction of tip speed ratio in wind turbines. Expert Syst Appl2010;
37: 5454–5460.
40.
Martínez-LucasGSarasúaJSánchez-FernándezJ.Frequency regulation of a hybrid windegulation 2.068org/in an isolated power system. Energies2018;
11: 239.
