Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon free Enabling resilient wide-area POD at BESS in Java, Indonesia 500 kV power grid

The future Indonesian power grid will have significant REGs, especially in Java Island. Wind and solar photovoltaic (PV) will be the dominating technologies in future Indonesian grid. Although REG can provide clean and sustainable energy, they also cause undesirable effects on system stability due to the uncertainty in their output and different dynamic characteristics. Battery energy storage system (BESS) has been considered as the promising candidate to manage the intermittency and low inertia associated with wind and PV in many future power systems. In addition to the normal functionality, the resilient wide-area power oscillation damping (POD) can be implemented in the BESS to damp the low-frequency oscillation in the system. This research proposes a method to design a resilient wide-area POD in BESS. A grey wolf optimiser (GWO) has been used to synthesise the resilient wide-area POD. The representative dynamic model of Java–Indonesian power system is used to evaluate the performance of the GWO-based resilient wide area POD. From the results, it is evident that the implementation of the proposed controller at BESS successfully damped the critical mode of the system. It is also observed that the proposed controller is robust against the failure of the input signal.

References

    1. 1)
      • 23. Surinkaew, T., Ngamroo, I.: ‘Hierarchical co-ordinated wide-area and local controls of DFIG wind turbine and PSS for robust power oscillation damping’, IEEE Trans. Sustain. Energy, 2016, 7, (3), pp. 943955.
    2. 2)
      • 13. Shen, Y., Yao, W., Wen, J., et al: ‘Resilient wide-area damping control for interarea oscillation considering communication failure’. IEEE Power and Energy Society General Meeting, Chicago, IL, USA, 2017.
    3. 3)
      • 10. Setiadi, H., Mithulananthan, N., Hossain, M.J.: ‘Impact of battery energy storage systems on electromechanical oscillations in power systems’. IEEE Power & Energy Society General Meeting, Chicago, IL, USA, 2017.
    4. 4)
      • 20. Lu, C.-F., Liu, C.-C., Wu, C.-J.: ‘Dynamic modelling of battery energy storage system and application to power system stability’, IEE Proc., Gener. Transm. Distrib., 1995, 142, (4), pp. 429435.
    5. 5)
      • 22. Ruan, S.-Y., Li, G.-J., Ooi, B.-T., et al: ‘Power system damping from real and reactive power modulations of voltage-source converter station’, IET Gener. Transm. Distrib., 2008, 2, (3), pp. 311320.
    6. 6)
      • 15. Kerdphol, T., Fuji, K., Mitani, Y., et al: ‘Optimization of a battery energy storage system using particle swarm optimization for stand-alone microgrids’, Int. J. Electr. Power Energy Syst., 2016, 81, pp. 3239.
    7. 7)
      • 12. Zhang, S., Vittal, V.: ‘Design of wide-area power system damping controllers resilient to communication failures’, IEEE Trans. Power Syst., 2013, 28, (4), pp. 42924300.
    8. 8)
      • 16. Zou, Y., He, J.: ‘Comprehensive modeling, simulation and experimental validation of permanent magnet synchronous generator wind power system’. IEEE/IAS 52nd Industrial and Commercial Power Systems Technical Conf. (I&CPS), Detroit, MI, USA, 2016.
    9. 9)
      • 5. Du, W., Bi, J., Wang, T., et al: ‘Impact of grid connection of large-scale wind farms on power system small-signal angular stability’, CSEE J. Power Energy Syst., 2015, 1, (2), pp. 8389.
    10. 10)
      • 1. ‘Peraturan Pemerintah Republik Indonesia No. 79 Tahun 2014 Tentang Kebijakan Energi Nasional’, ed: Jakarta, 2014.
    11. 11)
      • 28. El-Zonkoly, A., Khalil, A., Ahmied, N.: ‘Optimal tuning of lead-lag and fuzzy logic power system stabilizers using particle swarm optimization’, Expert Syst. Appl., 2009, 36, (2), pp. 20972106.
    12. 12)
      • 17. WECC guide for representation of photovoltaic systems in large-scale load flow simulation’. WECC Renewable Energy Modeling Task Force Report, 2010.
    13. 13)
      • 11. Yongli, Z., Chengxi, L., Bin, W., et al: ‘Damping control for a target oscillation mode using battery energy storage’, J. Mod. Power Syst. Clean Energy, 2018, 6, (4), pp. 833845.
    14. 14)
      • 18. Standard report for variable generation’. NERC Special Report, Atlanta, GA, USA, 2010.
    15. 15)
      • 2. Gautam, D., Vittal, V., Harbour, T.: ‘Impact of increased penetration of DFIG-based wind turbine generators on transient and small signal stability of power systems’, IEEE Trans. Power Syst., 2009, 24, (3), pp. 14261434.
    16. 16)
      • 21. Preece, R., Milanovic, J.V., Almutairi, A.M., et al: ‘Damping of inter-area oscillations in a mixed AC/DC networks using WAMS based supplementary controller’, IEEE Trans. Power Syst., 2013, 28, (2), pp. 11601169.
    17. 17)
      • 25. Shakarami, M.R., Davoudkhani, I.F.: ‘Wide-area power system stabilizer design based on grey wolf optimization algorithm considering the time delay’, Electr. Power Syst. Res., 2016, 133, pp. 149159.
    18. 18)
      • 31. Mohanty, S., Subudhi, B., Ray, P.K.: ‘A new MPPT design using grey wolf optimization technique for photovoltaic system under partial shading conditions’, IEEE Trans. Sustain. Energy, 2016, 7, (1), pp. 181188.
    19. 19)
      • 9. Prajapati, P., Parmar, A.: ‘Multi-area load frequency control by various conventional controller using battery energy storage system’. Int. Conf. on Energy Efficient Technologies for Sustainability (ICEETS), Nagercoil, India, 2016.
    20. 20)
      • 8. Hung, D.Q., Mithulananthan, N., Bansal, R.: ‘Integration of PV and BES units in commercial distribution systems considering energy loss and voltage stability’, Appl. Energy, 2014, 113, pp. 11621170.
    21. 21)
      • 6. Setiadi, H., Krismanto, A.U., Mithulananthan, N., et al: ‘Modal interaction of power systems with high penetration of renewable energy and BES systems’, Int. J. Electr. Power Energy Syst., 2018, 97, pp. 385395.
    22. 22)
      • 7. Krismanto, A., Mithulananthan, N., Kamwa, I.: ‘Oscillatory stability assessment of microgrid in autonomous operation with uncertainties’, IET Renew. Power Gener., 2017, 12, (4), pp. 494504.
    23. 23)
      • 27. Mirjalili, S., Mirjalili, S.M., Lewis, A.: ‘Grey wolf optimizer’, Adv. Eng. Softw., 2014, 69, pp. 4661.
    24. 24)
      • 32. Setiadi, H., Mithulananthan, N., Krismanto, A.U., et al: ‘Low-frequency oscillatory stability study on 500 kV Java-Indonesian electric grid’. 27th Int. Symp. on Industrial Electronics (ISIE), Cairns, QLD, Australia, 2018.
    25. 25)
      • 24. Philipp, L.D., Mahmood, A., Philipp, B.L.: ‘An improved refinable rational approximation to the ideal time delay’, IEEE Trans. Circuits Syst. I, Fundam. Theory Appl., 1999, 46, (5), pp. 637640.
    26. 26)
      • 4. Eftekharnejad, S., Vittal, V., Heydt, G.T., et al: ‘Small signal stability assessment of power systems with increased penetration of photovoltaic generation: a case study’, IEEE Trans. Sustain. Energy, 2013, 4, (4), pp. 960967.
    27. 27)
      • 19. Clark, K., Miller, N.W., Walling, R.: ‘Modelling of GE solar photovoltaic plants for grid studies’. General Electrical International, Inc., Schenectady, NY, USA, 2010.
    28. 28)
      • 3. Hasan, K.N., Preece, R.: ‘Influence of stochastic dependence on small-disturbance stability and ranking uncertainties’, IEEE Trans. Power Syst., 2018, 33, (3), pp. 32273235.
    29. 29)
      • 26. Abdillah, M., Soeprijanto, A., Purnomo, M.H., et al: ‘A novel design of WACS based multi-output support vector machine (M-SVM) for oscillation damping on power system’. Int. Conf. on Information Technology and Electrical Engineering (ICITEE), Yogyakarta, Indonesia, 2013.
    30. 30)
      • 30. Long, W., Jiao, J., Liang, X., et al: ‘Inspired grey wolf optimizer for solving large-scale function optimization problems’, Appl. Math. Model., 2018, 60, pp. 112126.
    31. 31)
      • 29. Djerioui, A., Houari, A., Ait-Ahmed, M., et al: ‘Grey wolf based control for speed ripple reduction at low speed operation of PMSM drives’, ISA Trans., 2018, 74, pp. 111119.
    32. 32)
      • 14. Shahgholian, G., Movahedi, A.: ‘Power system stabiliser and flexible alternating current transmission systems controller coordinated design using adaptive velocity update relaxation particle swarm optimisation algorithm in multi-machine power system’, IET Gener. Transm. Distrib., 2016, 10, (8), pp. 18601868.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2018.6670
Loading

Related content

content/journals/10.1049/iet-gtd.2018.6670
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address