Dynamic Analysis and Optimal Design of FLPSS for Power Network Connected Solid Oxide Fuel Cell Using of PSO

Document Type : Research paper


1 Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran

2 Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran.


This paper studies the theory and modeling manner of solid oxide fuel cell (SOFC) into power network and its effect on small signal stability. The paper demonstrates the fundamental module, mathematical analysis and small signal modeling of the SOFC connected to single machine infinite bus (SMIB) system. The basic contribution of the study is to attenuate the low frequency oscillations by optimal stabilizers in the presence of SOFC. To optimize the performance of system, fuzzy logic-based power system stabilizer (FLPSS) is exploited and designed by particle swarm optimization (PSO) technique. To ensure the effectiveness of the proposed optimal stabilizers, the simulation process takes in three scenarios of operating conditions. The effectiveness of proposed PSO based FLPSS on the oscillations in the power system, including SOFC is extensively demonstrated through time-domain simulations and by comparing FLPSS with the results of other stabilizers approaches. 


Main Subjects

[1]       J. Larminie and A. Dicks., Fuel Cell System Explained, 2nd. New York, Wiley, 2002.
[2]       M. Farooque and H. C. Maru., “Fuel cells-the clean and efficient power generators,” Proc.IEEE, vol. 89, no.12, pp. 1819-1829, 2001.
[3]       B. Raton, Fuel Cell Technology Handbook., FL: CRC, 2002.
[4]       P. Thounthong, B. Davat, S. Rael, P. Sethakul., “Fuel cell high-power applications,” IEEE Ind. Electron. Mag., vol. 3, no. 1: pp. 32-46, 2009.
[5]       Y. H. Li, S. Rajakaruna and S. S. Choi., “Control of a solid oxide fuel cell power plant in a grid-connected system,” IEEE Trans. Energy Coners., vol. 22, no. 2, pp. 405-413, 2007.
[6]       J. Padulle’s, G. W. Ault, and J. R. McDonald., “An integrated SOFC plant dynamic model for power systems simulation,” J. Power Sources, vol. 86, pp. 495-500, 2000.
[7]       K. Sedghisigarchi and A. Feliachi., “Dynamic and transient analysis of power distribution systems with fuel cells–part I: fuel-cell dynamic model,” IEEE Trans. Energy Convers., vol. 19, no. 2, pp. 423-428, 2004.
[8]       K. Sedghisigarchi and A. Feliachi., “Dynamic and transient analysis of power distribution systems with fuel cells–part II: control and stability enhancement,” IEEE Trans. Energy Convers., vol. 19, no. 2, pp. 429-434, 2004.
[9]       S. Das, D. Das and A. Patra., “Operation of solid oxide fuel cell based distributed generation,” Energy Procedia, vol. 31; pp. 439-447, 2009.
[10]    E. M. Fleming and I. A. Hiskens., “Dynamics of a microgrid supplied by solid oxide fuel cells in bulk power system dynamics and control-VII.” IEEE Revitalizing Oper. Reliab., vol. 19, pp. 1-10, 2007.
[11]    H. Wang and G. Li., “Dynamic performance of microturbine and fuel cell in a microgrid,” Proc. Int. Conf. Mechatron. Sci. Electr. Eng. Comput., pp. 122-125, 2011.
[12]    W. Du, H. F. Wang, X.F. Zhang and L.Y. Xiao., “Effect of grid-connected solid oxide fuel cell power generation on power systems small-signal stability,” IET Renew. Power Gener., vol. 6, no.1, pp. 24-37, 2012.
[13]    C. J. Hatziadoniu, A. A. Lobo, F. Pourboghrat and M. Daneshdoost., “A simplified dynamic model of grid-connected fuel-cell generators,” IEEE Trans. Power Delivery, vol. 17, no. 2, pp. 467-473, 2002.
[14]    P. Kunder, Power system stability and control, McGraw-Hill, 1994.
[15]    X. Yang and A. Feliachi., “Stabilization of inter-area oscillation modes through excitation systems,” IEEE Trans. Power Syst., vol. 9, no.1, pp.494-502, 1994.
[16]    M. Klein, G. J. Roger and P. Kundur., “A fundamental study of inter-area oscillations in power systems,” IEEE Trans. Power Syst., vol. 6, no. 3, pp. 914-921, 1991.
[17]    A. M. El-Zonkoly, A. A. Khalil and N. M. Ahmied., “Optimal tuning of lead-lag and fuzzy logic power system stabilizers using particle swarm optimization,” Expert Syst. Appl. ,vol. 36, no. 2, pp. 2097-2106, 2009.
[18]    K. Mazlumi, M. Darabian and M. Azari., “Adaptive fuzzy synergetic PSS design to damp power system oscillations,” J. Oper. Autom. Power Eng., vol. 1, no. 1, pp. 43-53, 2013.
[19]    Y. N. Yu, Electric power system dynamics, Academic Press, Inc., 111 FIFTH AVE., NEW YORK, NY 10003, USA, 1983.
[20]    M. R. Banaei., “Multi-Stage DC-AC Converter Based on new DC-DC converter for energy conversion,” J. Oper. Autom. Power Eng., vol. 4, no. 1, pp. 42-53, 2016.
[21]    CIGRE technical report: Modeling of power electronics equipment (FACTS) in load flow and stability programs, CIGRE T F 38-01-08, 1998.
[22]    J. Kennedy and R. Eberhart., “Particle swarm optimization,” Proc. IEEE Int. Conf. Neural Networks, vol. 4, pp. 1942-1948, 1995.
[23]    A. Jalilvand, A. Safari and R. Aghmasheh, “Design of state feedback stabilizer for multi-machine power system using PSO algorithm,” Proc. IEEE Int. Conf. Multitopic, 2008, pp. 1-6.
[24]    M. Rahmati, R. Effatnejad and A. Safari, “Comprehensive learning particle swarm optimization for multi-objective optimal power flow,” Indian J. Sci. Technol., vol. 7, no. 3, pp. 262-270, 2014.
[25]    A. Safari, N. Rezaei, “Towards an extended power system stability: An optimized GCSC-based inter-area damping controller proposal,” Int. J. Electr. Power Energy Syst., vol. 56, pp. 316-324, 2014.
Volume 5, Issue 2
December 2017
Pages 215-225
  • Receive Date: 29 April 2017
  • Revise Date: 05 June 2017
  • Accept Date: 01 July 2017
  • First Publish Date: 01 December 2017