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access icon free Proficient load-frequency regulation of demand response supported bio-renewable cogeneration based hybrid microgrids with quasi-oppositional selfish-herd optimisation

This is an earliest attempt to study the effective regulation of load-frequency oscillations due to the penetration of renewable generations in bio-renewable cogeneration based hybrid microgrids with demand response (DR) support considering optimal utilisation of resources. The work is a maiden attempt to derive the linearised model of a medium-sized linear-Fresnel-reflector type solar-thermal power unit for load-frequency study in the proposed wind/micro-hydro/biogas/biodiesel generator-based hybrid microgrids, modelling suitable DR strategies for both isolated and interconnected modes. The proposed systems are simulated using MATLAB/Simulink for coordinated source/demand-side management, proposing a novel quasi-oppositional selfish-herd optimisation algorithm in both the modes, incorporating real-time recorded solar/wind data and realistic random loads. Firstly, the oscillations due to renewable-penetrations are reduced efficiently in the isolated microgrid incorporating biodiesel generator and DR supports. Then the study is further extended for interconnected two-unequal hybrid microgrids considering resource availabilities. The system responses are compared in four extreme scenarios of source variations, as well as three variations of DRs without retuning the controllers to study the adaptability of the proposed system. Finally, the system frequency oscillations are regulated satisfactorily by DR support for both the modes.

References

    1. 1)
      • 20. Kundur, P.: ‘Control of active power and reactive power’, in Neal J., Balu, Mark G., Lauby (Eds.): ‘Power system stability and control’, (McGraw-Hill, New York, NY, USA, 1994, reprint 2009), pp. 581627.
    2. 2)
      • 2. Nguyen, M.H., Saha, T.K., Eghbal, M.: ‘Impact of high level of renewable energy penetration on inter-area oscillation’. 21st Australasian Universities IEEE Power Engineering Conf. (AUPEC), Brisbane, QLD, Australia, September 2011, pp. 16.
    3. 3)
      • 21. Buzás, J.: ‘Block-oriented modeling of solar thermal systems’. Doctoral thesis, Szent Istvan University, Godollo, Hungary, 2009, pp. 710.
    4. 4)
      • 11. Barik, A.K., Das, D.C.: ‘Expeditious frequency control of solar photovoltaic/biogas/biodiesel generator based isolated renewable microgrid using grasshopper optimisation algorithm’, IET Renew. Power Gener., 2018, 12, (14), pp. 16591667.
    5. 5)
      • 9. Cocco, D., Serra, F.: ‘Performance comparison of two-tank direct and thermocline thermal energy storage systems for 1 MWe class concentrating solar power plants’, Energy, 2015, 81, pp. 526536.
    6. 6)
      • 7. Das, D.C., Sinha, N., Roy, A.K.: ‘Automatic generation control of an organic Rankine cycle solar–thermal/wind–diesel hybrid energy system’, Energy Technol., 2014, 2, (8), pp. 721731.
    7. 7)
      • 13. Barik, A.K., Das, D.C.: ‘Optimal load-frequency regulation of Bio-renewable cogeneration based interconnected hybrid microgrids with demand response support’. 15th IEEE India Council Int. Conf. (INDICON), Coimbatore, India, December 2018, pp. 16.
    8. 8)
      • 19. Shankar, G., Mukherjee, V.: ‘Quasi oppositional harmony search algorithm based controller tuning for load frequency control of multi-source multi-area power system’, Int. J. Electr. Power Energy Syst., 2016, 75, pp. 289302.
    9. 9)
      • 20. Kundur, P.: ‘Control of active power and reactive power’, in Neal J., Balu, Mark G., Lauby (Eds.): ‘Power system stability and control’, (McGraw-Hill, New York, 1994, reprint 2009), pp. 581627.
    10. 10)
      • 15. Latif, A., Das, D.C., Ranjan, S., et al: ‘Comparative performance evaluation of WCA-optimized Non-integer controller employed with WPG-DSPG-PHEV based isolated 2-area interconnected microgrid system’, IET Renew. Power Gener., 2019, 13, (5), pp. 725736.
    11. 11)
      • 22. Lee, D. J., Wang, L.: ‘Small-signal stability analysis of an autonomous hybrid renewable energy power generation/energy storage system part I: time-domain simulations’, IEEE Trans. Energy Convers., 2008, 23, (1), pp. 311320.
    12. 12)
      • 16. Hasanien, H.M., El-Fergany, A.A.: ‘Symbiotic organisms search algorithm for automatic generation control of interconnected power systems including wind farms’, IET Gener. Transm. Distrib., 2017, 11, (7), pp. 16921700.
    13. 13)
      • 12. Barik, A.K., Das, D.C.: ‘Active power management of isolated renewable microgrid generating power from rooftop solar arrays, sewage waters and solid urban wastes of a smart city using SSA’. Int. Conf. on Technologies for Smart-City Energy Security and Power (ICSESP), Bhubaneswar, India, March 2018, pp. 16.
    14. 14)
      • 4. Bao, Y.Q., Li, Y., Hong, Y.Y., et al: ‘Design of a hybrid hierarchical demand response control scheme for the frequency control’, IET Gener. Transm. Distrib., 2015, 9, (15), pp. 23032310.
    15. 15)
      • 21. Buzás, J.: ‘Block-oriented modeling of solar thermal systems’. Doctoral thesis, Szent Istvan University, Godollo, 2009, pp. 710.
    16. 16)
      • 10. El-Fergany, A.A., El-Hameed, M.A.: ‘Efficient frequency controllers for autonomous two-area hybrid microgrid system using social-spider optimiser’, IET Gener. Transm. Distrib., 2017, 11, (3), pp. 637648.
    17. 17)
      • 18. Fausto, F., Cuevas, E., Valdivia, A., et al: ‘A global optimization algorithm inspired in the behavior of selfish herds’, Biosystems, 2017, 160, pp. 3955.
    18. 18)
      • 1. Tucho, G.T., Nonhebel, S.: ‘Alternative energy supply system to a rural village in Ethiopia’, Energy Sustain. Soc., 2017, 7, (1), p. 33.
    19. 19)
      • 3. He, P., Wen, F., Ledwich, G., et al: ‘Small signal stability analysis of power systems with high penetration of wind power’, J. Mod. Power Syst. Clean Energy, 2013, 1, (3), pp. 241248.
    20. 20)
      • 8. Cau, G., Cocco, D.: ‘Comparison of medium-size concentrating solar power plants based on parabolic trough and linear Fresnel collectors’, Energy Procedia, 2014, 45, pp. 101110.
    21. 21)
      • 14. Tripathy, D., Barik, A.K., Choudhury, N.B.D., et al: ‘Performance comparison of SMO-based fuzzy PID controller for load frequency control’. Soft Computing for Problem Solving, Singapore, 2019, pp. 879892.
    22. 22)
      • 6. Das, D.C., Roy, A.K., Sinha, N.: ‘GA based frequency controller for solar thermal–diesel–wind hybrid energy generation/energy storage system’, Int. J. Electr. Power Energy Syst., 2012, 43, (1), pp. 262279.
    23. 23)
      • 5. Bao, Y.Q., Li, Y., Wang, B., et al: ‘Demand response for frequency control of multi-area power system’, J. Mod. Power Syst. Clean Energy, 2017, 5, (1), pp. 2029.
    24. 24)
      • 2. Nguyen, M.H., Saha, T.K., Eghbal, M.: ‘Impact of high level of renewable energy penetration on inter-area oscillation’. 21st Australasian Universities IEEE Power Engineering Conf. (AUPEC), Brisbane, Australia, September 2011, pp. 16.
    25. 25)
      • 17. Othman, A.M., El-Fergany, A.A.: ‘Design of robust model predictive controllers for frequency and voltage loops of interconnected power systems including wind farm and energy storage system’, IET Gener. Transm. Distrib., 2018, 12, (19), pp. 42764283.
    26. 26)
      • 23. NASA Surface meteorology and Solar Energy - Available Tables’. Available at https://eosweb.larc.nasa.gov/cgi-bin/sse/grid.cgi?&num=266111&lat=20.296&hgt=100&submit=Submit&veg=17&sitelev=&email=skip@larc.nasa.gov&p=grid_id&step=2&lon=85.825, accessed 27 April 2018.
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