Abstract
In this paper, we propose a methodology to tune power system stabilizers and thyristor-controlled series capacitor damping controllers simultaneously. The particle swarm optimization algorithm is incorporated into a power system model to tune the parameters of supplementary damping controllers. A test power system of 10 generators, 39 buses and 46 transmission lines is simulated to validate the use of this optimization algorithm. The tuning of supplementary damping controllers using the proposed methodology increases their performance to provide additional damping to low-frequency oscillation modes in the simulated power system. The controller position is determined by the participation factors (power system stabilizers) and the distance between the interest pole and the zero of the open-loop transfer function of the power oscillation damping controller (thyristor-controlled series capacitor-power oscillation damping). The results show the operating efficiency of the power system after using the optimization technique to tune damping parameters, thereby improving power system integrity. The power sensitivity model is used for the simulations presented in this work focusing on the analysis small-signal stability.
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References
Abido, M. (2002). Optimal design of power-system stabilizers using particle swarm optimization. IEEE Transactions on Energy Conversion, 17(3), 406–413. doi:10.1109/TEC.2002.801992.
Araujo, P. B., & Zaneta, L. C. (2001). Pole placement method using the system matrix transfer function and sparsity. International Journal of Electric Power System & Energy Systems, 23(3), 173–178.
Basler, M., & Schaefer, R. (2008). Understanding power-system stability. IEEE Transactions on Industry Applications, 44(2), 463–474.
Bratton, D., & Kennedy, J. (2007). Defining a standard for particle swarm optimization. In Swarm intelligence symposium-SIS, Honolulu, pp. 120–127.
Gurrala, G., & Sen, I. (2010). Power system stabilizers design for interconnected power systems. IEEE Transactions on Power Systems, 25(2), 1042–1051. doi:10.1109/TPWRS.2009.2036778.
Hassan, L. H., Moghavvemi, M., Almurib, H. A., & Steinmayer, O. (2013). Application of genetic algorithm in optimization of unified power flow controller parameters and its location in the power system network. International Journal of Electrical Power & Energy Systems, 46, 89–97.
IEEE STANDARDS. (2009). IEEE recommended practice for specifying thyristor-controlled series capacitors, New York. doi:10.1109/IEEESTD.2009.5340372.
Jabr, R., Pal, B., Martins, N., & Ferraz, J. (2010). Robust and coordinated tuning of power system stabiliser gains using sequential linear programming. Generation, Transmission and Distribution, 4(8), 893–904. doi:10.1049/iet-gtd.2009.0669.
Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization. In IEEE international conference on neural networks, Perth, vol. 4, pp. 1942–1948.
Kundur, P. (1994). Power system stability and control. New York: McGraw-Hill.
Mahapatra, S., & Jha, A. (2012). PSS & TCSC coordinated design using particle swarm optimization for power system stability analysis. In 2012 2nd International conference on power, control and embedded systems (ICPCES), pp. 1–5. doi:10.1109/ICPCES.2012.6508094.
Meikandasivam, S., Nema, R. K., & Jain, S. K. (2010). Performance of installed TCSC projects. In International conference on power electronics, New Delhi, pp. 1–8.
Menezes, M. M., Araujo, P. B., & Fortes, E. V. (2014). Bacterial foraging optimization algorithm used to adjust the parameters of power system stabilizers and thyristor controlled series capacitor-power oscillation damping controller, pp. 1–6. doi:10.1109/INDUSCON.2014.7059408.
Milano, F. (2010). Power system modelling and scripting. Berlin, Heidelberg, New York: Springer.
Molina, D., Venayagamoorthy, G., Liang, J., & Harley, R. (2013). Intelligent local area signals based damping of power system oscillations using virtual generators and approximate dynamic programming. IEEE Transactions on Smart Grid, 4(1), 498–508. doi:10.1109/TSG.2012.2233224.
Morsali, J., Kazemzadeh, R., & Azizian, M. (2013). Coordinated design of MPSS and TCSC-based damping controller using PSO to enhance multi-machine power system stability. In 2013 21st Iranian conference on electrical engineering (ICEE), pp. 1–6.
Moura, R. F., Furini, M. A., & Araujo, P. B. (2012). Estudo das limitações impostas ao amortecimento de oscilações eletromecânicas pelos zeros da FTMA de controladores suplementares. Controle & Automação, 23(2), 190–201.
Rogers, G. (2000). Power system oscillations. New York: Springer.
Sen, K., & Sen, M. (2009). Introduction to FACTS controllers. Hoboken, NJ: IEEE Press/Wiley.
Shayeghi, H., Safari, A., & Shayanfar, H. (2010). PSS and TCSC damping controller coordinated design using PSO in multi-machine power system. Energy Conversion and Management, 51(12), 2930–2937.
Simoes, A., Savelli, D., Pellanda, P., Martins, N., & Apkarian, P. (2009). Robust design of a TCSC oscillation damping controller in a weak 500-kV interconnection considering multiple power flow scenarios and external disturbances. IEEE Transactions on Power Systems, 24(1), 226–236. doi:10.1109/TPWRS.2008.2006999.
Talaq, J. (2012). Optimal power system stabilizers for multi machine systems. International Journal of Electric Power System & Energy Systems, 43(1), 793–803.
Zhang, J., Chung, C., & Han, Y. (2012). A novel modal decomposition control and its application to PSS design for damping interarea oscillations in power systems. IEEE Transactions on Power Systems, 27(4), 2015–2025. doi:10.1109/TPWRS.2012.2188820.
Zhang, X. P., Rehtanz, C., & Pal, B. (2006). FACTS-devices and applications. Berlin, Heidelberg: Springer.
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de Menezes, M.M., de Araujo, P.B. & do Valle, D.B. Design of PSS and TCSC Damping Controller Using Particle Swarm Optimization. J Control Autom Electr Syst 27, 554–561 (2016). https://doi.org/10.1007/s40313-016-0257-z
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DOI: https://doi.org/10.1007/s40313-016-0257-z