Published

2017-05-01

Rapid generation of control parameters of Multi-Infeed system through online simulation

Rápida generación de parámetros de control del sistema Multi-Infeed a través de la simulación online

DOI:

https://doi.org/10.15446/ing.investig.v37n2.61822

Keywords:

HVDC, PSO, ISE, objective function, Proportional Integral (PI) controller. (en)
HVDC, PSO, ISE, función objetivo, sistema integral de control (PI). (es)

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Authors

  • Rasool Aazim State Key Laboratory of Alternate Renewable Energy, School of Electrical and Electronic Engineering, North China Electric Power University
  • Chongru Liu State Key Laboratory of Alternate Renewable Energy, School of Electrical and Electronic Engineering, North China Electric Power University, Beijing
  • Rasool Haaris National University of Computer and Emerging Sciences Islamabad Pakistan
  • Asif Mansoor Department of Electronics System Engineering, Hanyang University, Republic of Korea.
Simulated Self-Generated - Particle Swarm optimization (SSG-PSO) toolbox that automatically generates PI control parameters very quickly in PSCAD is designed. This toolbox operates by utilizing transient simulation to evaluate objective function and converges the fitness values of objective function through PSO algorithm during run time simulation of Multi-infeed HVDC systems. Integral Square Error-Objective Function (ISE-OF) is used to accomplish the task. To make the toolbox faster, ranges are set for PSO generated value that limit the time of data acquisition for the objective function by only considering transition time of a system. This toolbox has a capability to optimize multiple controllers at same time. The PI values are generated faster and the results are showing markedly improved performance of a system during startup and under fault condition. The experimental results are presented in this paper.
Se ha diseñado una caja de herramientas de optimización por enjambre de partículas simulado autogenerado que, automáticamente, genera parámetros de control PI de manera rápida en PSCAD. Esta caja de herramientas funciona mediante el uso de la simulación de transitorios para evaluar la función objetivo, y converge los valores de aptitud de la función objetivo a través del algoritmo PSO durante la simulación de tiempo de ejecución de los sistemas HVDC de alimentación múltiple. Aquí, la función de error cuadrático integral (ISE-OF) se utiliza para realizar esta tarea. Para hacer la caja de herramientas más rápida, se establecieron rangos para el valor gene ado PSO que limitan el tiempo de adquisición de datos para la función objetivo considerando únicamente el tiempo de transición de un sistema. Además, esta caja tiene la capacidad de optimizar varios controladores al mismo tiempo. Los valores de PI se generan más rápidamente y los resultados dejan ver un rendimiento notablemente mejorado de un sistema durante el arranque y, en condiciones de falla. En el presente trabajo se muestran los resultados experimentales.

References

AlRashidi, M. R., & El-Hawary, M. E. (2009). A survey of particle swarm optimization applications in electric power systems. IEEE Transactions on Evolutionary Computation, 13(4), 913-918.

BINGÜL, Z., & Karahan, O. (2012). Fractional PID controllers tuned by evolutionary algorithms for robot trajectory control. Turkish Journal of Electrical Engineering & Computer Sciences, 20(Sup. 1), 1123-1136.

Center, M. H. (1998). PSCAD/EMTDC User’s Manual. Manitoba HVDC Center, Winnipeg, Canada.

Chen, H., Li, J., & Zhou, X. (2012). PSO-based self-tuning PI control for STATCOM. Paper presented at the Power Electronics and Motion Control Conference (IPEMC), 2012 7th International.

Eberhart, R. C., & Kennedy, J. (1995). A new optimizer using particle swarm theory. Paper presented at the Proceedings of the sixth international symposium on micro machine and human science.

Filizadeh, S., Gole, A. M., Woodford, D. A., & Irwin, G. D. (2007). An optimization-enabled electromagnetic transient simulation-based methodology for HVDC controller design. IEEE transactions on power delivery, 22(4), 2559- 2566.

Gahramani, H., Lak, A., Farsadi, M., & Hosseini, H. (2013). Mitigation of SSR and LFO with a TCSC based conventional damping controller optimized by the PSO algorithm and a fuzzy logic controller. Turkish Journal of Electrical Engineering & Computer Sciences, 21(5), 1302-1317.

Gaing, Z.-L. (2004). A particle swarm optimization approach for optimum design of PID controller in AVR system. IEEE transactions on energy conversion, 19(2), 384-391.

Gole, A. M., Filizadeh, S., Menzies, R. W., & Wilson, P. L. (2003). Electromagnetic transients simulation as an objective function evaluator for optimization of power system performance. Paper presented at the Proceedings of the International Conference on Power System Transients (IPST’03).

Gole, A. M., Filizadeh, S., Menzies, R. W., & Wilson, P. L. (2005). Optimization-enabled electromagnetic transient simulation. IEEE transactions on power delivery, 20(1), 512-518.

Gole, A. M., Filizadeh, S., & Wilson, P. L. (2005). Inclusion of robustness into design using optimization-enabled transient simulation. IEEE transactions on power delivery, 20(3), 1991-1997.

Khorramabadi, S. S., & Bakhshai, A. (2015). Critic-based self-tuning PI structure for active and reactive power control of VSCs in microgrid systems. IEEE Transactions on Smart Grid, 6(1), 92-103.

Kumar, N., Kumar, V., & Tyagi, B. (2016). Optimization of PID parameters using BBBC for a multiarea AGC scheme in a deregulated power system. Turk J Elec Eng & Comp Sci, 4105 – 4116.

Liu, C.-H., & Hsu, Y.-Y. (2012). Design of a self-tuning PI controller for a STATCOM using particle swarm optimization. IEEE Transactions on industrial Electronics, 57(2), 702-715.

Ortiz, P., & Ramos-Paja, C. (2015). Auto-tuning of PV controllers to improve the speed response and stability of the P&O algorithm. Ingeniería e Investigación, 35, 5-12.

Shi, Y., & Eberhart, R. (1998). A modified particle swarm optimizer. Paper presented at the Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on.

Van den Bergh, F., & Engelbrecht, A. P. (2006). A study of particle swarm optimization particle trajectories. Information sciences, 176(8), 937-971.

Woodford, D. A., Gole, A. M., & Menzies, R. W. (1983). Digital simulation of dc links and ac machines. IEEE Transactions on Power Apparatus and Systems, 6(PAS-102), 1616-1623.

Yoshida, H., Kawata, K., Fukuyama, Y., Takayama, S., & Nakanishi, Y. (2000). A particle swarm optimization for reactive power and voltage control considering voltage security assessment. IEEE Transactions on power systems, 15(4), 1232-1239.

Zhang, Y., & Liu, C. (2012). Parameters Optimal Design of HVDC PI Controller Based on APSO Algorithm. Paper presented at the 2012 Asia-Pacific Power and Energy Engineering Conference.

Zhao, C., Lu, X., & Li, G. (2007). Parameters optimization of VSC-HVDC control system based on simplex algorithm. Paper presented at the Power Engineering Society General Meeting, 2007. IEEE.

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How to Cite

Aazim, R., Liu, C., Haaris, R., & Mansoor, A. (2017). Rapid generation of control parameters of Multi-Infeed system through online simulation. Ingeniería E Investigación, 37(2), 67-73. https://doi.org/10.15446/ing.investig.v37n2.61822
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Copyright (c) 2017 Rasool Aazim, Chongru Liu, Rasool Haaris, Asif Mansoor

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