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Introduction

  • Stefan PaszekEmail author
  • Andrzej Boboń
  • Sebastian Berhausen
  • Łukasz Majka
  • Adrian Nocoń
  • Piotr Pruski
Chapter
  • 250 Downloads
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 631)

Abstract

This chapter contains a general description of the developed methods and tools supporting the measurement process of determining reliable values of mathematical model parameters of generating unit elements, in particular synchronous generators and excitation systems. Special measuring tests are the basis for determining the parameters. They can be carried out under normal operating conditions of generating units, in which the magnetic cores of electric machines (synchronous generators and electromachine excitation systems) are saturated and the signals in voltage regulators may reach the limits. In this chapter, there is also a short description of selected methods, known from the literature, for determining (estimating) the parameters of mathematical models of synchronous generators. In the further part of this chapter, the content of this monograph with division into chapters is presented.

Keywords

Synchronous generator models Excitation system models Measurement parameter estimation 

References

  1. 1.
    Abd-Alla AN, Cheng SJ, Wen JY, Zhang J (2006) Model parameter identification of excitation system based on a genetic algorithm techniques. Paper presented at the power system technology. International conference on power system technology, pp 1–5Google Scholar
  2. 2.
    Ahmadi SS, Karrari M (2011) Nonlinear identification of synchronous generators using a local model approach. Przegląd Elektrotechniczny 8:166–170Google Scholar
  3. 3.
    Anderson PM, Fouad AA (2003) Power system control and stability. Wiley Inc.Google Scholar
  4. 4.
    Arjona MA, Hernandez C, Cisneros-Gonzalez M, Escarela-Perez R (2012) Estimation of synchronous generator parameters using the standstill step-voltage test and a hybrid genetic algorithm. Electr Power Energy Syst 35:105–111CrossRefGoogle Scholar
  5. 5.
    Berhausen S, Paszek S (2010) Use of pseudorandom signal for electromagnetic parameter estimation of synchronous generator with static exciter working in a power system. Paper presented at the 33-th international conference on fundamentals of electrotechnics and circuit theory, SPETO’2010, Ustroń, pp 69–70Google Scholar
  6. 6.
    Berhausen S, Paszek S (2015) Use of the finite element method for parameter estimation of the circuit model of a high power synchronous generator. Bull Pol Acad Sci 63(3):575–582Google Scholar
  7. 7.
    Berhausen S, Paszek S (2015) Assessment of the accuracy of synchronous generator model parameter estimation based on noisy dynamic waveforms. Przegląd Elektrotechniczny 7:16–20Google Scholar
  8. 8.
    Berhausen S, Paszek S (2016) Synchronous generator model parameter estimation based on noisy dynamic wave forms. J Electr Eng 67(1):21–28.  https://doi.org/10.1515/jee-2016-0003/CrossRefGoogle Scholar
  9. 9.
    Bertini S, Fracchia M, Mariscotti A, Pierrat L (1998) Determination of model parameters for solid rotor synchronous machine from standstill tests. Paper presented at the international conference on electrical machines, Istanbul, ICEM’98, 2–4 Sept 1998, pp 2111–2115Google Scholar
  10. 10.
    Bhatti MA (2000) Practical optimization methods. With mathematica applications. Springer, New YorkCrossRefGoogle Scholar
  11. 11.
    Białek J, Paszek S, Boboń A, Kudła J (2002) Synchronous machine parameter derivation program. Project ECP1219/C3762 sponsored by EPRI Solutions, Electric Power Research Institute, Inc. (Contractor: University of Durham, School of Engineering, Durham, UK), Paolo Alto, USAGoogle Scholar
  12. 12.
    Bissig H, Reichert K, Kulig T (1993) Modelling and identification of synchronous machines, a new approach with an extended frequency range. IEEE Trans Energy Convers 8(2):263–271CrossRefGoogle Scholar
  13. 13.
    Boboń A, Bojarska M, Kraszewski T, Majka Ł, Pasko M, Paszek S, Pruski P (2012) Computations of generating unit model parameters using program PARZW with database. Paper presented at the 10th international conference control of power systems, CPS, Tatranské Matliare, High Tatras, Slovak Republic, 15–17 May 2012, pp 169–170Google Scholar
  14. 14.
    Boboń A, Paszek S, Pruski P, Kraszewski T, Bojarska M (2011) Computer-aided determining of parameters of generating unit models based on measurement tests. Przegląd Elektrotechniczny 87(5):17–21Google Scholar
  15. 15.
    Boboń A, Paszek S, Pruski P, Kraszewski T, Bojarska M (2010) Matlab/simulink program for determining parameter of generating unit models. Paper presented at the computational problems of electrical engineering, CPEE, Lazne Kynzvart, Czech Republic, Sept 2010, p 75Google Scholar
  16. 16.
    Boboń A, Paszek S, Pruski P, Nocoń A (2012) Comparison of parameter estimation results of different models of synchronous generator working in thermal power plant. Paper presented at the 35-th international conference on fundamentals of electrotechnics and circuit theory, IC-SPETO, 23–26 May 2012, pp 115–116Google Scholar
  17. 17.
    Boboń A, Nocoń A, Paszek S, Pruski P (2017) Determination of synchronous generator nonlinear model parameters based on power rejection tests using a gradient optimization algorithm. Bull Pol Acad Sci 65(4):479–488.  https://doi.org/10.1515/bpasts-2017-0053CrossRefGoogle Scholar
  18. 18.
    Bortoni EC, Jardini JA (2002) Identification of synchronous machine parameters using load rejection test data. IEEE Trans Energy Convers 17(2):242–247CrossRefGoogle Scholar
  19. 19.
    Chen WK (1995) The circuits and filters handbook. CRC PressGoogle Scholar
  20. 20.
    Cisneros-Gonzalez M, Hernadez C, Morales-Caporal R, Bonilla-Huerta E, Arjona MA (2013) Parameter estimation of a synchronous-generator two-axis model based on the chirp test. IEEE Trans Energy Convers 28(1):44–51CrossRefGoogle Scholar
  21. 21.
    Dandeno PL, Hauth RL, Schulz RP (1979) Effects of synchronous machine modelling in large scale system studies. IEEE Trans Power Apparatus Syst PAS 92(2):574–582 (1973)Google Scholar
  22. 22.
    de Mello FP, Hannett LH (1981) Validation of synchronous machine models and derivation of model parameters from tests. IEEE Trans Power Apparatus Syst 100(2):662–672Google Scholar
  23. 23.
    de Mello FP, Ribeiro JR (1977) Derivation of synchronous machine parameters from tests. IEEE Trans Power Apparatus Syst PAS 96(4):1211–1218Google Scholar
  24. 24.
    Dehghani M, Karrari M, Rosehart W, Malik OP (2010) Synchronous machine model parameters estimation by a time-domain identification method. Electr Power Energy Syst 32:524–529CrossRefGoogle Scholar
  25. 25.
    Feltes JW, Lima LTG (2003) Validation of dynamic model parameters for stability analysis: industry need, current practices and future trends. Paper presented at the IEEE power engineering society general meeting, vol 3, 13–17 July 2003, pp 1295–1301Google Scholar
  26. 26.
    Feltes JW, Orero S, Fardanesh B, Uzunovic E, Zelingher S, Abi-Samra N (2002) Deriving model parameters from field test measurements. IEEE Comput Appl Power 30–36Google Scholar
  27. 27.
    Firouzi BB, Jamshidpour E, Niknam T (2008) A new method for estimation of large synchronous generator parameters by genetic algorithm. World Appl Sci J 326–331Google Scholar
  28. 28.
    Gallehdari Z, Dehghani M, Nikravesh SKY (2014) Online state space model parameter estimation in synchronous machines. Iran J Electr Electron Eng 10(2):124–132Google Scholar
  29. 29.
    Glaninger-Katschning A (2009) Identification of excitation system transfer functions in hydro power plants using a binary pseudo random signal. Elektrotech Intech. Springer, Berlin, pp 8–12Google Scholar
  30. 30.
    Hannett LN, Feltes JW, Fardanesh B (1994) Field tests to validate hydro turbine-governor model structure and parameters. IEEE Trans Power Syst 9(4):1744–1751CrossRefGoogle Scholar
  31. 31.
    Hasni M, Touhami O, Ibtiouen R, Fadel M, Caux S (2010) Estimation of synchronous machine parameters by standstill tests. Math Comput Simul 81:277–289MathSciNetCrossRefGoogle Scholar
  32. 32.
    Hasni M, Touhami O, Ibtiouen R, Fadel M, Caux S (2007) Synchronous machine parameter identification by various excitation signals. Electr Eng 219–228.  https://doi.org/10.10007/s00202-007-0069-z
  33. 33.
    Hemandez JA, Botero HA, Ospina JD, Perez JC (2006) Excitation System parameters estimation using evolutionary algorithms. Paper presented at the transmission and distribution conference and exposition, Latin America, TDC 2006, pp 1–6Google Scholar
  34. 34.
    Hutchison G, Zahawi B, Harmer K, Gadoue S, Giaouris D (2015) Non-invasive identification of turbogenerator parameters from actual transient network data. Gener Transm Distrib IET 9(11):1129–1136CrossRefGoogle Scholar
  35. 35.
    IEEE Guide (1995) IEEE Guide: Test procedures for synchronous machines. IEEE Standard 115–1995Google Scholar
  36. 36.
    IEEE Standard (1987) IEEE standard procedures for obtaining synchronous machine parameters by standstill frequency response testing. IEEE Standard 115A–1987Google Scholar
  37. 37.
    IEEE Committee Report (1973) IEEE committee report: dynamic models for steam and hydro turbines in power system studies. IEEE Trans. Power Apparatus Syst PAS 92(6):1904–1915Google Scholar
  38. 38.
    IEEE Standard 421.5 (2016) IEEE recommended practice for excitation system models for power system stability studies. IEEE Standard 421.5Google Scholar
  39. 39.
    IEEE Std 1110–2002 (2003) IEEE guide for synchronous generator modeling practices and applications in power system stability analyses. IEEE Std 1110–2002, 11Google Scholar
  40. 40.
    Jahromi ME, Firouzi B, Ranjbar AM (2006) Possibility of large synchronous generator parameters estimation via on-line field tests using genetic algorithm. Paper presented at the IEEE power India conference, 10-12 Apr 2006, p 6Google Scholar
  41. 41.
    Khereshki NI, Choolabi EF, Shahalami SH (2017) Identification of dynamic parameters of a fourth-order synchronous generator nonlinear model using particle swarm optimization algorithm. Paper presented at the 2017 Iranian conference on electrical engineering, Teheran, Iran, 2–4 May 2017, pp 1170–1174Google Scholar
  42. 42.
    Kou P, Zhou J, Wang Ch, Xiao H, Zhang H, Li Ch (2011) Parameters identification of nonlinear state space model of synchronous generator. Eng Appl Artif Intell 24:1227–1237CrossRefGoogle Scholar
  43. 43.
    Kraszewski T, Majka Ł, Pasko M, Paszek S (2010) Sensitivity analysis of the electromachine excitation system model. Paper presented at the 9th international conference control of power systems, CPS, Tatranske Matliare, Slovak Republic, May 2010, pp 29–30Google Scholar
  44. 44.
    Losada RA (2003) Practical FIR filter design in MATLAB. Revision 1.0. The MathWorks, Inc., Massachusetts, USA, 1–31Google Scholar
  45. 45.
    Lyons RG (2011) Understanding digital signal processing, 3rd edn. Prentice HallGoogle Scholar
  46. 46.
    Machowski J, Bialek J, Bumby J (2008) Power system dynamics. Stability and control. Wiley, Chichester-New YorkGoogle Scholar
  47. 47.
    Majka Ł, Paszek S (2010) Sensitivity analysis of the steam turbine and its governor mathematical model. Paper presented at the 33th international conference on fundamentals of electrotechnics and circuit theory, SPETO, Ustroń, May 2010, pp 67–68Google Scholar
  48. 48.
    Majka Ł, Paszek S (2009) Use of selected optimisation algorithm for estimation of excitation system model parameters. Paper presented at the advanced methods of the theory of electrical engineering AMTEE, Cheb, Czech Republic, Sept 2009, pp IV-7–IV-8Google Scholar
  49. 49.
    Majka Ł, Paszek S (2010) Algorithms for estimation of models parameters of excitation system of an electrical machine. Acta Technica CSAV, Acad Sci Czech Repub 55(2):179–194Google Scholar
  50. 50.
    Majka Ł, Paszek S (2016) Mathematical model parameter estimation of a generating unit operating in the polish national power system. Bull Pol Acad Sci 64(2):409–416Google Scholar
  51. 51.
    Mertins A (1999) Signal analysis: wavelets, filter banks, time-frequency transforms and applications. Wiley, New York, USACrossRefGoogle Scholar
  52. 52.
    Nocoń A, Pasko M, Paszek S (2010) Sensitivity analysis including uncertainty of synchronous generator model parameter. Paper presented at the 9th international conference control of power systems, CPS, Tatranske Matliare, Slovak Republic, May 2010, pp 27–28Google Scholar
  53. 53.
    Nocoń A, Paszek S (2011) Sensitivity analysis of power system stability factors including the uncertainty of mathematical model parameters. Zeszyty Naukowe Politechniki Śląskiej seria „Elektryka” 218(2):7–17Google Scholar
  54. 54.
    Oppenheim AV, Schafer RW (1974) Digital signal processing. Prentice Hall, Englewood CliffszbMATHGoogle Scholar
  55. 55.
    Oteafy AMA, Chiasson JN (2014) A standstill parameter identification technique for the divided winding rotor synchronous generator. Paper presented at the IEEE international conference power and energy, 1-3 Dec 2014, pp 99–104Google Scholar
  56. 56.
    Paszek S, Boboń A, Kudła J, Białek J, Abi-Samra N (2005) Parameter estimation of the mathematical model of a generator, excitation system and turbine. Przegląd Elektrotechniczny 81(11):7–12Google Scholar
  57. 57.
    Paszek S, Majka Ł (2008) Computations of the model parameters of generating unit elements based on measurements. AT&P J Plus 2, Power Syst Stab 49–53Google Scholar
  58. 58.
    Paszek S, Nocoń A (2014) Optimisation and polyoptimisation of power system stabilizer parameters. Lambert Academic Publishing, Saarbrücken, GermanyGoogle Scholar
  59. 59.
    Paszek S, Nocoń A (2015) Parameter polyoptimization of PSS2A power system stabilizers operating in a multi-machine power system including the uncertainty of model parameters. Appl Math Comput 267:750–757.  https://doi.org/10.1016/j.amc.2014.12.013
  60. 60.
    Pruski P, Paszek S (2018) Calculations of power system electromechanical eigenvalues based on analysis of instantaneous power waveforms at different disturbances. Appl Math Comput 319:104–114.  https://doi.org/10.1016/j.amc.2017.01.057MathSciNetCrossRefzbMATHGoogle Scholar
  61. 61.
    Strauss JM, Vermeulen HJ, Coker ML (2002) Field Experience with PRBS Perturbation of a 133 MVA Hydro-Generator. Paper presented at the 6th IEEE AFRICON Conference in Africa, Vol.2, 2–4 October 2002, pp. 803-806Google Scholar
  62. 62.
    Vermeulen HJ, Strauss JM, Shikoana V (2002) Online estimation of synchronous generator parameters using PRBS perturbations. IEEE Trans Power Syst 17(3):674–700CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Stefan Paszek
    • 1
    Email author
  • Andrzej Boboń
    • 2
  • Sebastian Berhausen
    • 3
  • Łukasz Majka
    • 4
  • Adrian Nocoń
    • 5
  • Piotr Pruski
    • 6
  1. 1.Faculty of Electrical EngineeringSilesian University of TechnologyGliwicePoland
  2. 2.Faculty of Electrical EngineeringSilesian University of TechnologyGliwicePoland
  3. 3.Faculty of Electrical EngineeringSilesian University of TechnologyGliwicePoland
  4. 4.Faculty of Electrical EngineeringSilesian University of TechnologyGliwicePoland
  5. 5.Faculty of Electrical EngineeringSilesian University of TechnologyGliwicePoland
  6. 6.Faculty of Electrical EngineeringSilesian University of TechnologyGliwicePoland

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