Flicker source detection including fixed speed wind turbines using empirical mode decomposition

Document Type : Article

Authors

Department of Electrical and Computer Engineering, Semnan University, Semnan, Postcode: 35131-19111, Iran

Abstract

This study describes an approach to identify multiple flicker sources at the point of common coupling (PCC). The voltage signals of different flicker sources such as the electrical arc furnace, the fixed-speed wind turbine, and the diesel-engine driven generator were recorded at the PCC. For this purpose, various aerodynamic and mechanical faults of a wind turbine such as wind shear and tower shadow, gearbox tooth-breaking, blade crash, pitch angle error and various mechanical faults of diesel-engine driven generator such as misfiring, exciter, and governor error, are considered. After acquiring voltage signals of various faults, the empirical mode decomposition (EMD) as a robust signal processing technique for extracting useful features was used. Then, for reducing required memory space and computational burden, the minimal-redundancy-maximal-relevance (MRMR) and the symmetric uncertainty (SU) as the feature selection methods were applied. Also, for increasing the efficiency of feature selection methods, the cooperative game-theoretic method was utilized. Afterward, two classifiers based on the Naive-Bayes and the support vector machine (SVM) are used to detect the faults. Simulation results are presented to validate the effectiveness of the proposed method.

Keywords

References

References:
1. Hou, S., Chu, Y., and Fei, J. "Adaptive type-2 fuzzy neural network inherited terminal sliding mode control for power quality improvement", IEEE Trans. Ind. Informatics, 17(11), pp. 7564-7574 (2021).
2. Narimani, M. and Hosseinian, H. "Investigation of harmonic effects in locational marginal pricing and developing a framework  for LMP calculation", Sci. Iran., 29(3), pp. 1537-1546 (2022).
3. Xu, J. and Liu, Y. "Voltage flicker mitigation strategy based on individual pitch control of wind turbine", 2021 13th Int. Conf. Meas. Technol. Mechatronics Autom., IEEE, pp. 459-462 (2021).
4. Denisov, E., Evdokimov, Y.K., Nigmatullin, R.R., et al. "Spectral method for PEMFC operation mode monitoring based on electrical  fluctuation analysis", Sci. Iran., 24(3), pp. 1437-1447 (2017).
5. Moreno, C.V., Duarte, H.A., and Garcia, J.U. "Propagation of  flicker in electric power networks due to wind energy conversions systems", IEEE Trans. Energy Convers., 17(2), pp. 267-272 (2002).
6. Samet, H., Khosravi, M., Ghanbari, T., et al. "A two-level neural network approach for  flicker source location", Comput. Electr. Eng., 92, 107157 (2021).
7. Moghadam Banaem, H. and Tousi, B. "A new approach for the simultaneous identification of the location and individual contribution of multiple flicker sources using the least number of monitoring points", Int. Trans. Electr. Energy Syst., 31(3), p. e12767 (2021).
8. Moghadam Banaem, H., Abbasi, M., and Tousi, B. "A new method with minimum number of monitoring points for  flicker source tracing by wavelet transform", Int. Trans. Electr. Energy Syst., 29(9), p. e12057 (2019).
9. Givi, H. and Hoseini, S.R.K. "An effective signature for detection of flicker sources in transmission networks using fast fourier transform", 2020 28th Iran. Conf. Electr. Eng., IEEE, pp. 1-6 (2020).
10. Moghadam Banayem, H., Doroudi, A., and Poormonfared Azimi, M. "Flicker source tracing by wavelet transform", Electr. Power Components Syst., 43(4), pp. 412-421 (2015).
11. Eghtedarpour, N., Farjah, E., and Khayatian, A. "Intelligent identification of  flicker source in distribution systems", IET Gener. Transm. Distrib., 4(9), pp. 1016-1027 (2010).
12. Thirumala, K., Pal, S., Jain, T., et al. "A classification method for multiple power quality disturbances using EWT based adaptive filtering and multiclass SVM", Neurocomputing, 334, pp. 265-274 (2019).
13. Zhang, S., Li, P., Zhang, L., et al. "Modified S transform and ELM algorithms and their applications in power quality analysis", Neurocomputing, 185, pp. 231-241 (2016).
14. Axelberg, P.G.V., Bollen, M.H.J., and Gu, I.Y.-H. "Trace of  flicker sources by using the quantity of  flicker power", IEEE Trans. Power Deliv., 23(1), pp. 465-471 (2007).
15. Kuwalek, P. "Trace of flicker sources by using nonparametric statistical analysis of voltage changes", 2020 19th Int. Conf. Harmon. Qual. Power, IEEE, pp. 1-6 (2020).
16. Fooladi, M. and Foroud, A.A. "Recognition and assessment of different factors which affect flicker in wind turbines", IET Renew. Power Gener., 10(2), pp. 250- 259 (2016).
17. Fooladi, M., Foroud, A.A., and Abdoos, A.A. "Detection and evaluation of effective factors on flicker phenomenon in diesel-engine driven generators", Appl. Therm. Eng., 113, pp. 1194-1207 (2017).
18. Hafiz, F., Swain, A., Naik, C., et al. "Efficient feature selection of power quality events using two dimensional (2D) particle swarms", Appl. Soft Comput., 81, 105498 (2019).
19. Leinonen, A. and Laketic, N. "Advanced technology to ensure EAF grid  flicker compliance", Proc. - 2018 IEEE Int. Conf. Environ. Electr. Eng. 2018 IEEE Ind. Commer. Power Syst. Eur. EEEIC/I CPS Eur. 2018 (2018).
20. Karimi, H., Simab, M., and Nafar, M. "Enhancement of power quality utilizing photovoltaic fed DSTATCOM based on zig-zag transformer and fuzzy controller", Sci. Iran., 29(5), pp. 2465-2479 (2022).
21. Altintas, E., Salor, O., Cadirci, I., et al. "A new flicker contribution tracing method based on individual reactive current components of multiple EAFs at PCC", IEEE Trans. Ind. Appl., 46(5), pp. 1746-1754 (2010).
22. Moradifar, A., Foroud, A.A., and Fouladi, M. "Identification of multiple harmonic sources in power system containing inverter-based distribution generations using empirical mode decomposition", IET Gener. Transm. Distrib., 13(8), pp. 1401-1413 (2019).
23. Sun, X., Liu, Y., Li, J., et al. "Using cooperative game theory to optimize the feature selection problem", Neurocomputing, 97, pp. 86-93 (2012).
24. Tiwari, V.K. and Gupta, A.R. "Application of SVC and STATCOM for Wind Integrated Power System", Recent Adv. Power Electron. Drives, J. Kumar and P. Jena, Eds., Springer Singapore, Singapore, pp. 181- 192 (2021).
25. Alam, M.J.E., Muttaqi, K.M., and Sutanto, D. "Battery energy storage to mitigate rapid voltage/power fluctuations in power grids due to fast variations of solar/wind outputs", IEEE Access, 9, pp. 12191-12202(2021).
26. Srensen, P., Andresen, B., Fortmann, J., et al. "Modular structure of wind turbine models in IEC 61400-27-1", 2013 IEEE Power Energy Soc. Gen. Meet., IEEE, pp. 1-5 (2013).
27. Mostafaeipour, A., Rezaei, M., Jahangiri, M., et al. "Feasibility analysis of a new tree-shaped wind turbine for urban application: A case study", Energy Environ., 31(7), pp. 1230-1256 (2020).
28. Lee, T. "Financial investment for the development of renewable energy capacity", Energy Environ., 32(6), pp. 1103-1116 (2021).
29. Jang, H. "Firm structure, scale economies, and productivity in the US electric power industry: A cost function analysis", Energy Environ., 32(5), pp. 834- 854 (2021).
30. Charles Rajesh Kumar, J., Vinod Kumar, D., Baskar, D., et al. "Offshore wind energy status, challenges, opportunities, environmental impacts, occupational health, and safety management in India", Energy Environ., 32(4), pp. 565-603 (2021).
31. Qolipour, M., Mostafaeipour, A., Saidi-Mehrabad, M., et al. "Prediction of wind speed using a new Greyextreme learning machine hybrid algorithm: A case study", Energy Environ., 30(1), pp. 44-62 (2019).
32. Albani, A., Ibrahim, M.Z., Yong, K.H., et al. "The wind energy potential in Kudat Malaysia by considering the levelized cost of energy for combined wind turbine capacities", Energy Environ., 32(7), pp. 1149- 1169 (2021).
33. Saneie, H., Daniar, A., and Nasiri-Gheidari, Z. "Design optimization of a low speed small scale modular axial flux permanent magnet synchronous generator for urban wind turbine application", Sci. Iran., 29(6), pp. 3326-3337 (2022).
34. Das, S., Karnik, N., and Santoso, S. "Time-domain modeling of tower shadow and wind shear in wind turbines", ISRN Renew. Energy, 2011, pp. 1-11 (2011).
35. Dolan, D.S.L. and Lehn, P.W. "Simulation model of wind turbine 3p torque oscillations due to wind shear and tower shadow", 2006 IEEE PES Power Syst. Conf. Expo., IEEE, pp. 2050-2057 (2006).
36. Wen, B., Wei, S., Wei, K., et al. "Power fluctuation and power loss of wind turbines due to wind shear and tower shadow", Front. Mech. Eng., 12(3), pp. 321-332 (2017).
37. Rao, S.S., Mechanical Vibrations, Addison-Wesley World Student Series, Addison-Wesley (1995).
38. Kim, S.-K. and Kim, E.-S. "PSCAD/EMTDC-based modeling and analysis of a gearless variable speed wind turbine", IEEE Trans. Energy Convers., 22(2), pp. 421-430 (2007).
39. Sitharthan, R., Geethanjali, M., and Karpaga Senthil Pandy, T. "Adaptive protection scheme for smart microgrid with electronically coupled distributed generations", Alexandria Eng. J., 55(3), pp. 2539-2550 (2016).
40. Casado, A.J., Nieto, F.J., Blazquez, F., et al. "A monitoring system for diesel engine driven generators based on electric power output oscillation assessment", IEEE Trans. Ind. Appl., 53(3), pp. 3182-3188 (2017).
41. Sezer, I. "A review study on using diethyl ether in diesel engines: effects on fuel properties, injection, and combustion characteristics", Energy Environ., 31(2), pp. 179-214 (2020).
42. Jhapte, R., Patel, R.N., and Neema, D.D., Design and Analysis of Optimized Hybrid Active Power Filter for Electric Arc Furnace Load, Springer, Singapore, pp. 250-258 (2018).
43. Hajipour, R., Asadollahzadeh Shamkhal, F., and Kobravi, H.R. "A methodology for examining the chaotic behavior of CoP signal during quiet standing based on empirical mode decomposition method", Sci. Iran., 28 (Special issue on collective behavior of nonlinear dynamical networks), pp. 1560-1569 (2021).
44. Hu, Z., Ma, J., Yang, L., et al. "Monthly electricity demand forecasting using empirical mode decompositionbased state space model", Energy Environ., 30(7), pp. 1236-1254 (2019).
45. Motlagh, S.Z.T. and Foroud, A.A. "Power quality disturbances recognition using adaptive chirp mode pursuit and grasshopper optimized support vector machines", Measurement, 168, 108461 (2021).
46. Moradifar, A., Foroud, A.A., and Firouzjah, K.G. "Comprehensive identification of multiple harmonic sources using fuzzy logic and adjusted probabilistic neural network", Neural Comput. Appl., 31(1), pp. 543-556 (2019).
47. Yu, J.C.P., Wee, H.M., Jeng, S., et al. "Two-stage game-theoretic approach to supplier evaluation, selection and order assignment", Sci. Iran., 28(6), pp. 3513-3524 (2021).
48. Gu, X., Guo, J., Xiao, L., et al. "Conditional mutual information-based feature selection algorithm for maximal relevance minimal redundancy", Appl. Intell., pp. 1-12 (2021).
49. Zhang, L. and Chen, X. "Feature selection methods based on symmetric uncertainty coefficients and independent classification information", IEEE Access, 9, pp. 13845-13856 (2021).
50. Rasaizadi, A., Sherafat, E., and Seyedabrishami, S. "Short-term prediction of traffic state, statistical approach versus machine learning approach", Sci. Iran., 29(3), pp. 1095-1106 (2022).
51. Das, S., Datta, S., Zubaidi, H.A., et al. "Applying interpretable machine learning to classify tree and utility pole related crash injury types", IATSS Res. (2021).
52. Putri, D.A., Kristiyanti, D.A., Indrayuni, E., et al. "Comparison of naive abyes algorithm and support vector machine using PSO feature selection for sentiment analysis on E-Wallet review", J. Phys. Conf. Ser., IOP Publishing, p. 12085 (2020).
53. Narayan, S. and Sathiyamoorthy, E. "A novel recommender system based on FFT with machine learning for predicting and identifying heart diseases", Neural Comput. Appl., 31(1), pp. 93-102 (2019).
54. Cervantes, J., Garcia-Lamont, F., Rodriguez- Mazahua, L., et al. "A comprehensive survey on support vector machine classification: Applications, challenges and trends", Neurocomputing, 408, pp. 189-215 (2020).
55. Mithulananthan, N., Hung, D.Q., and Lee, K.Y., Intelligent Network Integration of Distributed Renewable Generation, Springer (2016).
Scientia Iranica
Volume 30, Issue 5
Transactions on Computer Science & Engineering and Electrical Engineering (D)
September and October 2023
Pages 1743-1763

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