Non-linear recurrent ANN-based LFC design considering the new structures of Q matrix

Non-linear recurrent ANN-based LFC design considering the new structures of Q matrix

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Generation, Transmission & Distribution — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

This paper presents the design of a non-linear recurrent artificial neural network (ANN) based load frequency control (LFC) of a two-area power system interconnected via HVDC tie-line in parallel with EHVAC line. The control design is based on the combination of robust LFC and optimisation of recurrent ANN so that designed LFC scheme is suitable to handle the diverse operating conditions of power system. The various structures of the state cost weighting matrix (Q), i.e. controllability and observability aspects which affect the dynamics of the power system are used for the LFC design. The feedback gains achieved by the implementation of robust LFC using the different structures of Q are used to effectively train the recurrent ANN-based LFC design and its performance is analysed with and without system non-linearity's for 1% step load disturbance in one of the control areas to show the superiority of one design over the others. The closed-loop system eigenvalues obtained for the system ensure the system stability. Furthermore, the recurrent ANN-based LFC performance is evaluated for the diverse system operating conditions and compared with multi-layer perceptron (MLP) ANN-based and conventional PI control schemes to demonstrate the effectiveness of proposed LFC design scheme.


    1. 1)
      • 1. Sanpei, M., Kakehi, A., Takeda, H.: ‘Application of multi-variable control for automatic frequency controller of HVDC transmission system’, IEEE Trans. Power Deliv., 1994, 9, (2), pp. 10631068.
    2. 2)
      • 2. Sharma, G., Ibraheem, N.K.R.: ‘Recurrent ANN based AGC of a two-area power system with DFIG based wind turbines considering asynchronous tie-lines’. IEEE Int. Conf. on Advances in Engineering and Technology Research (ICAETR-2014), 2014, pp. 15.
    3. 3)
      • 3. Sahu, B.K., Pati, T.K., Nayak, J.R., et al: ‘A novel hybrid LUS-TLBO optimized fuzzy-PID controller for load frequency control of multi-source power system’, Int. J. Electr. Power Energy Syst., 2016, 74, pp. 5869.
    4. 4)
      • 4. Bevrani, H., Hiyama, T.: ‘Intelligent automatic generation control’ (CRC Press, 2011).
    5. 5)
      • 5. Bansal, R.C., Bhatti, T.S.: ‘Small signal analysis of isolated hybrid power systems: reactive power and frequency control analysis’ (Alpha Science International, Oxford, U.K., 2008).
    6. 6)
      • 6. Bansal, R.C.: ‘Automatic reactive power control of autonomous hybrid power systems’. PhD thesis, Indian Institute of Technology (IIT), Delhi, India, April 2003.
    7. 7)
      • 7. Sharma, G.: ‘Some investigations on AGC of interconnected power systems’. PhD thesis, Malaviya National Institute of Technology (NIT), Jaipur, India, July 2015.
    8. 8)
      • 8. Mohanty, B., Hota, P.K.: ‘Comparative performance analysis of fruit fly optimization algorithm for multi-area multi-source automatic generation control under deregulated environment’, IET Gener. Transm. Distrib, 2015, 9, (14), pp. 18451855.
    9. 9)
      • 9. Tarkeshwar, M., Mukherjee, V.: ‘Quasi-oppositional harmony search algorithm and fuzzy logic controller for load frequency stabilization of an isolated hybrid power system’, IET Gener. Transm. Distrib, 2015, 9, (5), pp. 427444.
    10. 10)
      • 10. Shree, B.S., Kamaraj, N.: ‘Hybrid neuro fuzzy approach for automatic generation control in restructured power system’, Int. J. Electr. Power Energy Syst., 2016, 74, pp. 274285.
    11. 11)
      • 11. Chaturvedi, D.K., Umrao, R., Malik, O.P.: ‘Adaptive polar fuzzy logic based load frequency controller’, Int. J. Electr. Power Energy Syst., 2015, 66, pp. 154159.
    12. 12)
      • 12. Willems, J.L.: ‘Sensitivity analysis of the optimum performance of conventional load frequency control’, IEEE Trans. Power Appar. Syst., 1974, PAS-93, (5), pp. 12871291.
    13. 13)
      • 13. Ibraheem, K.P., Kothari, D.P.: ‘Recent philosophies of automatic generation control strategies in power systems’, IEEE Trans. Power Syst., 2005, 20, (1), pp. 346357.
    14. 14)
      • 14. Fosha, C.E., Elgerd, O.I.: ‘The megawatt frequency control problem: A new approach via optimal control theory’, IEEE Trans. Power Appar. Syst., 1970, PAS-89, (4), pp. 563577.
    15. 15)
      • 15. Liaw, C.M., Chao, K.H.: ‘On the design of an optimal automatic generation controller for an interconnected power system’, Int. J. Control, 1993, 58, pp. 113127.
    16. 16)
      • 16. Ibraheem, K.P., Hasan, N., Singh, Y.: ‘Optimal automatic generation control of interconnected power system with asynchronous tie-lines under deregulated environment’, Electr. Power Compon. Syst., 2012, 40, pp. 12081228.
    17. 17)
      • 17. Ibraheem, N.K.R., Sharma, G.: ‘Study on dynamic participation of wind turbines in AGC of power system’, Electr. Power Compon. Syst., 2014, 43, (1), pp. 4455.
    18. 18)
      • 18. Sharma, G.I, Niazi, K.R.: ‘Optimal AGC of asynchronous power systems using output feedback control strategy with dynamic participation of wind turbines’, Electr. Power Compon. Syst., 2015, 43, (4), pp. 384398.
    19. 19)
      • 19. Parmar, K.P.S., Majhi, S., Kothari, D.P.: ‘Load frequency control of a realistic power system with multi-source power generation’, Int. J. Electr. Power Energy Syst., 2012, 42, pp. 426433.
    20. 20)
      • 20. Sharma, G., Ibraheem, K.R.N., Bansal, R.C.: ‘Optimal AGC of multi-area power system with parallel AC/DC lines using output vector feedback control strategy’, Int. J. Electr. Power Energy Syst., 2016, 81, pp. 2231.
    21. 21)
      • 21. Wang, Y., Zhou, R., Wen, C.: ‘Robust load-frequency controller design for power system’, IEE Proc. C, 1993, 140, (1), pp. 1116.
    22. 22)
      • 22. Athans, M., Falb, P.: ‘Optimal control: an introduction to theory and its application’ (McGraw-Hill, New York, 1966).
    23. 23)
      • 23. Latsman, G., Sinha, N., Rozsa, P.: ‘On the selection of states to be retained in a reduced order model’, IEE Proc. D, 1984, 131, pp. 1522.
    24. 24)
      • 24. Geromel, J.C., Peres, P.L.: ‘Decentralized load frequency control’, IEE Proc. D, 1985, 132, (5), pp. 225230.
    25. 25)
      • 25. Ahamed, T.P.I., Rao, P.S.N., Sastry, P.S.: ‘A reinforcement learning approach to automatic generation control’, Electr. Power Syst. Res., 2002, 63, (1), pp. 926.
    26. 26)
      • 26. Ahamed, T.P.I., Rao, P.S.N., Sastry, P.S.: ‘Reinforcement learning controllers for automatic generation control in power systems having reheat units with GRC and dead-band’, Int. J Power Energy Syst., 2006, 26, (2), pp. 137146.
    27. 27)
      • 27. Demiroren, A., Sengor, N.S., Zeynelgil, H.: ‘Automatic generation control by using ANN technique’, Electr. Power Compon. Syst., 2001, 29, (10), pp. 883896.
    28. 28)
      • 28. Demiroren, A., Sengor, N.S., Zeynelgil, H.: ‘Automatic generation control for power system with SMES by using neural network controller’, Electr. Power Compon. Syst., 2003, 31, (1), pp. 125.
    29. 29)
      • 29. Padhy, N.P.: ‘Artificial intelligence & intelligent systems’ (Oxford University Press, 2005).

Related content

This is a required field
Please enter a valid email address