Algoritmo de Otimização por Enxame de Partículas Paralelo para Minimização de Perdas de Potência Ativa em Sistemas Elétricos de Potência
Abstract
With the increase in electricity demand and, consequently, the complexity of operation and control of electric power systems in recent decades, studies for reducing active power loss in these systems have followed. Using the IEEE models of 14, 30 and 57 bus, this study aims to evaluate the applicability of GPU computing (Graphic Process Unit) specifically CUDA (Compute Unified Device Architecture), in this area. Performing a critical analysis of bioinspired strategies used in parallel architecture in order to minimize the loss of active power in electric power systems. It was observed from the results that the use of GPU computing shows promise when the mesh size is increased.
References
Christie, R. D. (2015). Power Systems Test Case Archive, University of Washington, Electrical Engineering. online: http://www.ee.washington.edu/research/pstca/.
De, M. and Goswami, S. (2014). Optimal reactive power procurement with voltage stability consideration in deregulated power system. Power Systems, IEEE Transactions on, 29(5):2078–2086.
Guo, C., Jiang, B., Yuan, H., Yang, Z., Wang, L., and Ren, S. (2012). Performance comparisons of parallel power flow solvers on gpu system. In RTCSA, pages 232–239. IEEE Computer Society.
Tadaiesky, V. W. A., Santana, A. L., Dias, L. d. J. C., Oliveira, I. d. I. d., Jacob Junior, A. F. L., and Lobato, F. M. F. (2013). Runtime performance evaluation of gpu and cpu using a genetic algorithm based on neighborhood model. In The 2013 International Conference on Parallel and Distributed Processing Techniques and Applications.
Yoshida, H., Kawata, K., Fukuyama, Y., Takayama, S., and Nakanishi, Y. (2000). A particle swarm optimization for reactive power and voltage control considering voltage security assessment. Power Systems, IEEE Transactions on, 15(4):1232–1239.
Zimmerman, R. D., Murillo-Sánchez, C. E., and Thomas, R. J. (2011). MATPOWER: Steady-State operations, planning, and analysis tools for power systems research and education. IEEE Trans. Power Syst., 26(1):12–19.
De, M. and Goswami, S. (2014). Optimal reactive power procurement with voltage stability consideration in deregulated power system. Power Systems, IEEE Transactions on, 29(5):2078–2086.
Guo, C., Jiang, B., Yuan, H., Yang, Z., Wang, L., and Ren, S. (2012). Performance comparisons of parallel power flow solvers on gpu system. In RTCSA, pages 232–239. IEEE Computer Society.
Tadaiesky, V. W. A., Santana, A. L., Dias, L. d. J. C., Oliveira, I. d. I. d., Jacob Junior, A. F. L., and Lobato, F. M. F. (2013). Runtime performance evaluation of gpu and cpu using a genetic algorithm based on neighborhood model. In The 2013 International Conference on Parallel and Distributed Processing Techniques and Applications.
Yoshida, H., Kawata, K., Fukuyama, Y., Takayama, S., and Nakanishi, Y. (2000). A particle swarm optimization for reactive power and voltage control considering voltage security assessment. Power Systems, IEEE Transactions on, 15(4):1232–1239.
Zimmerman, R. D., Murillo-Sánchez, C. E., and Thomas, R. J. (2011). MATPOWER: Steady-State operations, planning, and analysis tools for power systems research and education. IEEE Trans. Power Syst., 26(1):12–19.
Published
2015-07-20
How to Cite
ARAÚJO, Igor; TADAIESKY, Vincent; CAVALCANTE, Iago; SANTANA, Ádamo.
Algoritmo de Otimização por Enxame de Partículas Paralelo para Minimização de Perdas de Potência Ativa em Sistemas Elétricos de Potência. In: WORKSHOP ON PERFORMANCE OF COMPUTER AND COMMUNICATION SYSTEMS (WPERFORMANCE), 14. , 2015, Recife.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2015
.
p. 182-186.
ISSN 2595-6167.
DOI: https://doi.org/10.5753/wperformance.2015.10409.
