access icon free Stability improvement of PV-BESS diesel generator-based microgrid with a new modified harmony search-based hybrid firefly algorithm

© The Institution of Engineering and Technology
Received 22/02/2016, Accepted 17/01/2017, Revised 02/12/2016, Published 20/01/2017

Using a new improved harmony search-based hybrid firefly algorithm (IHBFA), a comprehensive controller gain parameter estimation of all distributed resources-based microgrid is proposed. To ensure a fast convergence and to endeavour less randomisation to conventional firefly algorithm (FA), diversity of population is increased by an improved harmony search (HS) algorithm. To decrease local optima searching delay, a linear incremental pitch adjustment rate and exponential decaying bandwidth is considered for proposed HS-based hybrid FA. Photovoltaic (PV), an auxiliary battery energy storage system (BESS) with the second-order phase-locked loop control, is considered as a primary DG (DG1) for the proposed microgrid. Padѐ approximation delay-based governor control is used for the diesel generator unit, considered as a secondary DG (DG2). The overall gain optimisation improves the dynamic stability limits by minimising low-frequency network behaviour. The effectiveness of proposed IHBFA in terms of power oscillation damping and improved stability limits is clearly demonstrated for microgrid applications.

Inspec keywords: approximation theory; minimisation; hybrid power systems; photovoltaic power systems; phase locked loops; power system dynamic stability; battery storage plants; diesel-electric generators; search problems; power generation control; distributed power generation

Other keywords: improved harmony search-based hybrid firefly algorithm; HS-based hybrid FA; dynamic stability improvement; linear incremental pitch adjustment rate; secondary DG; low-frequency network behaviour minimisation; gain optimisation; primary DG; IHBFA; power oscillation damping; Pade approximation delay-based governor control; auxiliary battery energy storage system; photovoltaic power system; second-order phase-locked loop control; exponential decaying bandwidth; distributed resources-based microgrid controller gain parameter estimation; optima searching delay; PV-BESS diesel generator-based microgrid stability improvement

Subjects: Combinatorial mathematics; Distributed power generation; Interpolation and function approximation (numerical analysis); Control of electric power systems; Stability in control theory; Interpolation and function approximation (numerical analysis); Solar power stations and photovoltaic power systems; Optimisation techniques; Combinatorial mathematics; Optimisation techniques; Secondary cells; Diesel power stations and plants

References

    1. 1)
      • 2. Li, X., Hui, D., Lai, X.: ‘Battery energy storage station (BESS)-based smoothing control of photovoltaic (PV) and wind power generation fluctuations’, IEEE Trans. Sustain. Energy, 2013, 4, (2), pp. 464–473.
    2. 2)
      • 16. Li, Q.: ‘Introduction to feedback control’ (Pearson Education India, 2010).
    3. 3)
      • 9. Daneshfar, F., Bevrani, H.: ‘Multiobjective design of load frequency control using genetic algorithms’, Int. J. Electric. Power Energy Syst., 2012, 42, (1), pp. 257–263.
    4. 4)
      • 17. Chassaing, R.: ‘Digital signal processing and applications with the C6713 and C6416 DSK’ (Wiley, New York, 2004).
    5. 5)
      • 11. Yang, X.S., He, X.: ‘Firefly algorithm: recent advances and applications’, Int. J. Swarm Intell., 2013, 1, (1), pp. 36–50.
    6. 6)
      • 12. Guo, L., Wang, G.-G., Wang, H., et al: ‘An effective hybrid firefly algorithm with harmony search for global numerical optimization’, Sci. World J., 2013, 2013, Article ID 125625, 9 pp..
    7. 7)
      • 1. Hassan, M.A., Abido, M.A.: ‘Optimal design of microgrids in autonomous and grid-connected modes using particle swarm optimization’, IEEE Trans. Power Electron., 2011, 26, (3), pp. 755–769.
    8. 8)
      • 10. Gaing, Z.L.: ‘A particle swarm optimization approach for optimum design of PID controller in AVR system’, IEEE Trans. Energy Conver., 2004, 19, (2), pp. 384–391.
    9. 9)
      • 7. Pogaku, N., Prodanović, M., Green, T.C.: ‘Modeling, analysis and testing of autonomous operation of an inverter-based microgrid’, IEEE Trans. Power Electron., 2007, 22, (2), pp. 613–625.
    10. 10)
      • 15. Geem, Z.W., Kim, J.H., Loganathan, G.V.: ‘A new heuristic optimization algorithm: harmony search’, Simulation, 2001, 76, (2), pp. 60–68.
    11. 11)
      • 5. Dhar, S., Dash, P.K.: ‘A finite time fast terminal sliding mode I–V control of grid-connected PV array’, J. Control Autom. Electric. Syst., 2015, 26, (3), pp. 314–335.
    12. 12)
      • 3. Mishra, S., Ramasubramanian, D., Sekhar, P.C.: ‘A seamless control methodology for a grid connected and isolated PV-diesel microgrid’, IEEE Trans. Power Syst., 2013, 28, (4), pp. 4393–4404.
    13. 13)
      • 14. Gardner, F.M.: ‘Phaselock techniques’ (John Wiley & Sons, 2005).
    14. 14)
      • 6. Tabesh, A., Iravani, R.: ‘Multivariable dynamic model and robust control of a voltage-source converter for power system applications’, IEEE Trans. Power Deliv., 2009, 24, (1), pp. 462–471.
    15. 15)
      • 18. Al Ameri, O., Boiko, I.: ‘Performance of optimal super-twisting controller for liquid level’, Asian J. Control , 2015, 18, pp. 1581–1590.
    16. 16)
      • 8. Katiraei, F., Iravani, M.R., Lehn, P.W.: ‘Small-signal dynamic model of a micro-grid including conventional and electronically interfaced distributed resources’, IET. Gener. Transm. Distrib., 2007, 1, (3), pp. 369–378.
    17. 17)
      • 4. Khajehoddin, S.A., Karimi-Ghartemani, M., Jain, P.K., et al: ‘A control design approach for three-phase grid-connected renewable energy resources’, IEEE Trans. Sustain. Energy, 2011, 2, (4), pp. 423–432.
    18. 18)
      • 13. Mauracher, P., Karden, E.: ‘Dynamic modelling of lead/acid batteries using impedance spectroscopy for parameter identification’, J. Power Sources, 1997, 67, (1), pp. 69–84.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-rpg.2016.0116
Loading

Related content

content/journals/10.1049/iet-rpg.2016.0116
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading