Advertisement

An Algorithm for Optimal Placement of Voltage Sag Monitors

  • Caio Marco dos Santos JunqueiraEmail author
  • Núbia Silva Dantas Brito
  • Benemar Alencar de Souza
  • Rodrigo de Almeida Coelho
  • Érica Mangueira Lima
Article
  • 10 Downloads

Abstract

Voltage sags are disturbances that deserve special attention in power quality (PQ) area, given its frequent occurrences. Their constant monitoring is, therefore, essential to diagnose its causes and mitigate economic losses of electric utility customers. However, the cost of a monitoring system may be excessive if not evaluated strategically. In this context, this work presents an algorithm for the installation of PQ monitors at strategic points of electric power distribution systems in order to diagnose voltage sags. Observability area concept and binary particle swarm optimization method were used to evaluate the problem. A sensitivity analysis was also performed, in which the influence of several parameters, such as fault resistance, system loading, detection threshold, fault type, and system expansion, was evaluated. The algorithm was validated in a Brazilian distribution system and in IEEE 34-bus system. The results indicated that the algorithm was able to detect voltage sags throughout the system using monitors at few buses, reducing the cost of the monitoring system.

Keywords

Power quality Voltage sags Observability Binary particle swarm optimization Sensitivity analysis 

Notes

Acknowledgements

The authors thank the Brazilian National Research Council (CNPq) and the Brazilian Improvement Coordination of Superior Level Personal (CAPES) for the financial support.

References

  1. Almeida, C. F. M. (2007). Methodology for the efficient monitoring of short duration voltage variations in power systems. Master’s thesis (in Portuguese).Google Scholar
  2. Bertho, R. et al. (2016). Optimized power quality monitor placement based on a particle swarm optimization algorithm. In 2016 17th international conference on harmonics and quality of power (ICHQP) (pp. 115–119).Google Scholar
  3. Costa, F. B., Souza, B. A. & Brito, N. S. D. (2010). Realtime detection of voltage sags based on wavelet transform. In 2010 IEEE/PES transmission and distribution conference and exposition: Latin America (TD-LA) (pp. 537–542).Google Scholar
  4. Daubechies, I. (1992). Ten lectures on wavelets. CBMS-NSF regional conference series. Philadelphia: SIAM.Google Scholar
  5. Dugan, R. C., et al. (2004). Electrical power systems quality (2nd ed.). New York: McGraw-Hill.Google Scholar
  6. Eldery, M. A., El-Saadany, F. & Salama, M. M. A. (2004). Optimum number and location of power quality monitors. In 11th international conference on harmonics and quality of power (pp. 50–57).Google Scholar
  7. EPRI. (2003). Distribution system power quality assessment: Phase II. Voltage sag and interruption analysis (pp. 5–17). Palo Alto: Electric Power Research Institute.Google Scholar
  8. Ibrahim, A. A., et al. (2012). A new approach for optimal power quality monitor placement in power system considering system topology. Przeglad Elektrotechniczny, 88, 272–276.Google Scholar
  9. IEEE. (2010). IEEE 34 node test feeder. Power System Analysis, Computing and Economics Committee.Google Scholar
  10. IEEE. (2014). IEEE guide for voltage sag indices. IEEE P1564/D19 (pp. 1–55).Google Scholar
  11. Juarez, E. E., Hernandez, A., & Olguin, G. (2009). An approach based on analytical expressions for optimal location of voltage sags monitors. IEEE Transactions on Power Delivery, 24(4), 2034–2042.CrossRefGoogle Scholar
  12. Kazemi, A., et al. (2013). Review of power quality monitor placement methods in transmission and distribution systems. Przeglad Elektrotechniczny, 89, 185–188.Google Scholar
  13. Kennedy, J. & Eberhart, R. (1995). Particle swarm optimization. In Proceedings, IEEE international conference on neural networks (Vol. 4, pp. 1942–1948).Google Scholar
  14. Khanesar, M. A., Teshnehlab, M., & Shoorehdeli, M. A. (2007). A novel binary particle swarm optimization. In Mediterranean conference on control automation, 2007. MED ’07 (pp. 1–6).Google Scholar
  15. Mali, V. P., Chakrasali, R. L., & Aprameya, K. S. (2015). A technical investigation of voltage sag. American Journal of Engineering Research (AJER), 4(10), 60–68.Google Scholar
  16. Mallat, S. G. (1989). A theory for multiresolution signal decomposition: The wavelet representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(7), 674–693.CrossRefzbMATHGoogle Scholar
  17. Martins, P. E. T., et al. (2018). Optimized allocation of power quality monitors in distribution systems considering fault location. In 2018 18th international conference on harmonics and quality of power (ICHQP) (pp. 1–6).Google Scholar
  18. Olguin, G., & Bollen, M. H. J. (2003). Optimal dips monitoring program for characterization of transmission system. In Power Engineering Society general meeting, 2003 (Vol. 4, p. 2490). IEEE.Google Scholar
  19. Olguin, G., Vuinovich, F., & Bollen, M. H. J. (2006). An optimal monitoring program for obtaining voltage sag system indexes. IEEE Transactions on Power Systems, 21(1), 378–384.CrossRefGoogle Scholar
  20. Santos, W. C., et al. (2010). Automatic building of a simulated high impedance fault database. In Transmission and distribution conference and exposition: Latin America.Google Scholar
  21. Santos, W. C., et al. (2017). High-impedance fault identification on distribution networks. IEEE Transactions on Power Delivery, 32(1), 23–32.CrossRefGoogle Scholar
  22. Solano, J. B., Petit-Suárez, J. F., & Ordóñez-Plata, G. (2015). Optimal placement of voltage sag monitors in smart distribution systems: Impact of the dynamic network reconfiguration. In 2015 IEEE PES innovative smart grid technologies Latin America (ISGT LATAM) (pp. 361–365).Google Scholar

Copyright information

© Brazilian Society for Automatics--SBA 2019

Authors and Affiliations

  1. 1.Power Systems Laboratory (LSP), Department of Electric Engineering (DEE)Federal University of Campina Grande (UFCG)Campina GrandeBrazil

Personalised recommendations