Power system security assessment with high wind penetration using the farms models based on their correlation

Power system security assessment with high wind penetration using the farms models based on their correlation

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Increasing the wind energy penetration in a power system presents some technical challenges to the transmission expansion planning (TEP). In the first stage of TEP, the transmission bottlenecks should be determined and ranked via security assessment. The high penetration of wind energy means a large number of wind farms exist in various geographic areas. It is found that there is a correlation between the wind speed series of different farms. Therefore, integration of the correlated wind farms into security assessment is addressed in this study. Hence, a new model of wind speed prediction is presented based on the correlated autoregressive moving average time series. The copula functions are used to make the predefined correlation among wind speed series. Here a linear correlation using a Gaussian copula is implemented. Then, the risk-based security assessment is performed using the proposed sequential time simulation. The proposed process is applied to the modified IEEE 39-bus test system which comprises 15 wind farms. Then, the transmission bottlenecks are identified and ranked regarding their overload risks. Finally, the impacts of the wind farms correlation on the risk index are investigated and those contingencies which impose the highest influence on this risk are identified.


    1. 1)
      • 1. Dudurych, I.M., Rogers, A., Aherne, R., et al: ‘Safety in numbers’, IEEE Power Energy Mag., 2012.
    2. 2)
      • 2. Yu, P., Venkatesh, B.: ‘Fast security and risk constrained probabilistic unit commitment method using triangular approximate distribution model of wind generators’, IET Gener. Transm. Distrib., 2014, 8, (11), pp. 17781788.
    3. 3)
      • 3. Xie, K., Li, Y., Li, W.: ‘Modelling wind speed dependence in system reliability assessment using copulas’, IET Renew. Power Gener., 2012, 6, (6), pp. 392399.
    4. 4)
      • 4. Chen, T.H., Tran, V.T.: ‘Optimization of transmission expansion planning by minimal cut sets based on graph theory’, Electr. Power Compon. Syst., 2015, 43, (16), pp. 18221831.
    5. 5)
      • 5. Dyer, J.: ‘U.S. Department of Energy Transmission Bottleneck Project Report’, Consortium For Electric Reliability Technology Solutions (CERTS), 2003.
    6. 6)
      • 6. Ciupuliga, A.R., Gibescu, M., Pelgrum, E.: ‘Round the year security analysis with large scale wind integration’, IEEE Trans. Sustain. Energy, 2012, 3, (1), pp. 8593.
    7. 7)
      • 7. Zheng, J., Wen, F., Ledwich, G.: ‘Risk control in transmission system expansion planning with wind generators’, Int. Trans. Electr. Energy Syst., 2014, 24, (2), pp. 227245.
    8. 8)
      • 8. Arabali, A., Ghofrani, M., Etezadi-Amoli, M., et al: ‘A multi-objective transmission expansion planning framework in deregulated power systems with wind generation’, IEEE Trans. Power Syst., 2014, 29, (6), pp. 30033011.
    9. 9)
      • 9. Moeini-Aghtaie, M., Abbaspour, A., Fotuhi-Firuzabad, M.: ‘Incorporating large-scale distant wind farms in probabilistic transmission expansion planning – part I: theory and algorithm’, IEEE Trans. Power Syst., 2012, 27, (3), pp. 15851593.
    10. 10)
      • 10. Hemmati, R., Hooshmand, R.A., Khodabakhshian, A.: ‘Market based transmission expansion and reactive power planning with consideration of wind and load uncertainties’, Renew. Sust. Energy Rev., 2014, 29, pp. 110.
    11. 11)
      • 11. Gupta, N.: ‘A review on the inclusion of wind generation in power system studies’, Renew. Sust. Energy Rev., 2016, 59, pp. 530543.
    12. 12)
      • 12. Billinton, R., Gao, R.Y.: ‘Multistate wind energy conversion system models for adequacy assessment of generating systems incorporating wind energy’, IEEE Trans. Energy Convers., 2008, 23, (1), pp. 163170.
    13. 13)
      • 13. Aghaebrahimi, M.R., Mehdizadeh, M., Heshmati, A., et al: ‘Introducing well being analysis for wind diesel islanded grid’, Int. Trans. Electr. Energy Syst., 2013, 23, (8), pp. 14901503.
    14. 14)
      • 14. Munoz, C., Sauma, E., Contreras, J., et al: ‘Impact of high wind power penetration on transmission network expansion planning’, IET Gener. Transm. Distrib., 2012, 6, (12), pp. 12811291.
    15. 15)
      • 15. Akbari, T., Rahimi Kian, A., Tavakoli Bina, M.: ‘Security constrained transmission expansion planning: a stochastic multi objective approach’, Electr. Power Energy Syst., 2012, 43, pp. 444453.
    16. 16)
      • 16. Ni, M., McCalley, J.D., Vittal, V., et al: ‘Online risk-based security assessment’, IEEE Trans. Power Syst., 2003, 18, (1), pp. 258265.
    17. 17)
      • 17. Lei, M., Shiyan, L., Chuanwen, J., et al: ‘A review on the forecasting of wind speed and generated power’, Renew. Sust. Energy Rev., 2009, 13, (4), pp. 915920.
    18. 18)
      • 18. Wen, J., Zheng, Y., Donghan, F.: ‘A review on reliability assessment for wind power’, Renew. Sust. Energy Rev., 2009, 13, (9), pp. 24852494.
    19. 19)
      • 19. Billinton, R., Chen, H., Ghajar, R.: ‘Time-series models for reliability evaluation of power systems including wind energy’, Microelectron. Reliab., 1996, 36, (9), pp. 12531261.
    20. 20)
      • 20. Teh, J., Cotton, I.: ‘Reliability impact of dynamic thermal rating system in wind power integrated network’, IEEE Trans. Reliab., 2016, 65, (2), pp. 10811089.
    21. 21)
      • 21. Ljung, L.: ‘System identification: theory for the user’ (Prentice Hall PTR, 1999).
    22. 22)
      • 22. Holttinen, H., Rissanen, S., Larsen, X., et al: ‘Wind and load variability in the Nordic countries’ (VTT Technical Research Centre of Finland, 2013).
    23. 23)
      • 23. Papaefthymiou, G.: ‘Integration of stochastic generation in power systems’ (Delft University of Technology, 2007).
    24. 24)
      • 24. Zhang, N., Kang, C., Xia, Q., et al: ‘Modeling conditional forecast error for wind power in generation scheduling’, IEEE Trans. Power Syst., 2014, 29, (3), pp. 13161324.
    25. 25)
      • 25. Li, Y., Xie, K., Hu, B.: ‘Copula-ARMA model for multivariate wind speed and its applications in reliability assessment of generating systems’, J. Electr. Eng. Technol., 2013, 8, (3), pp. 421427.
    26. 26)
      • 26. Shargh, S., Khorshid ghazani, B., Mohammadi ivatl, B.: ‘Probabilistic multi-objective optimal power flow considering correlated wind power and load uncertainties’, Renew. Energy, 2016, 94, pp. 1021.
    27. 27)
      • 27. Hu, X., He, J., Ly, H.: ‘Generating multivariate nonnormal distribution random numbers based on copula function’, J. Inf. Comput. Sci., 2007, 2, (3), pp. 191196.
    28. 28)
      • 28. Ellis, A., Nelson, R., Engeln, E.V., et al: ‘Reactive power performance requirements for wind and solar plants’. IEEE Power and Energy Society General Meeting, San Diego, 2012.
    29. 29)
      • 29. Jayaweera, D.S.: ‘Value of security assessment – extensions and applications’. PhD Thesis, UMIST University, Manchester, 2003.
    30. 30)
      • 30. Billinton, R., Li, W.: ‘Reliability assessment of electric power systems using Monte Carlo methods’ (Springer, 1994).
    31. 31)
      • 31. Wood, A.J., Wollenberg, B.F.: ‘Power generation operation and control’ (John Wiley & Sons, 1984).
    32. 32)
      • 32. Kothari, D.P., Nagrath, I.J.: ‘Modern power system analysis’ (McGraw-Hill Education, 2003).
    33. 33)
      • 33. Hamona, C., Perningeb, M., Soder, L.: ‘An importance sampling technique for probabilistic security assessment in power systems with large amounts of wind power’, Electr. Power Syst. Res., 2016, 131, pp. 1118.
    34. 34)
      • 34. Kundur, P., Paserba, J., Ajjarapu, V., et al: ‘Definition and classification of power system stability (IEEE/CIGRE joint task force on stability terms and definitions)’, IEEE Trans. Power Syst., 2004, 19, (2), pp. 13871401.
    35. 35)
      • 35. Aghaebrahimi, M.R., Mehdizadeh, M.: ‘A new procedure in reliability assessment of wind-diesel islanded grid’, Electr. Power Compon. Syst., 2011, 39, (14), pp. 15631576.
    36. 36)
      • 36. IEEE Reliability Test System Task Force of the Application of Probability Methods Subcommittee: ‘The IEEE reliability test system’, IEEE Trans. Power Syst., 1999, 14, (3), pp. 10101020.
    37. 37)
      • 37. Bills, G.W.: ‘On line stability analysis study’ (Edison Electric Institute, 1970).
    38. 38)
      • 38. ‘North Dakota agriculture weather network’,

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