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Probabilistic Fuzzy Approach to Assess RDS Vulnerability and Plan Corrective Action Using Feeder Reconfiguration

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DOI: 10.4236/epe.2012.45043    3,450 Downloads   4,924 Views   Citations

ABSTRACT

Two common problems for a typical Power distribution system are voltage collapse & instability. Challenge is to identify the vulnerable nodes and apply the effective corrective actions. This paper presents a probabilistic fuzzy approach to assess the node status and proposes feeder reconfiguration as a method to address the same. Feeder reconfiguration is altering the topological structures of distribution feeders by changing the open/closed states of the sectionalizing and ties switches. The solution is converge using a probabilistic fuzzy modeled solution, which defines the nodal vulnerability index (VI) as a function of node voltage and node voltage stability index and predicts nodes critical to voltage collapse. The information is further used to plan best combination of feeders from each loop in distribution system to be switched out such that the resulting configuration gives the optimal performance i.e. best voltage profile and minimal kW losses. The proposed method is tested on established radial distribution system and results are presented.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

M. Thomas, R. Ranjan and R. Raina, "Probabilistic Fuzzy Approach to Assess RDS Vulnerability and Plan Corrective Action Using Feeder Reconfiguration," Energy and Power Engineering, Vol. 4 No. 5, 2012, pp. 330-338. doi: 10.4236/epe.2012.45043.

References

[1] B. Venkatesh and R. Ranjan, “Optimal Radial Distribution System Reconfiguration Using Fuzzy Adaptation of Evolutionary Programming,” Electrical power and energy systems, Vol. 25, No. 10, 2003, pp. 775-780.
[2] T. Asakura, T. Genji, T. Yura, N. Hayashi and Y. Fukuyama, “Long Term Distribution Network Expansion Planning by Network Reconfiguration and Generation of Construction Plans,” IEEE Transactions on Power Systems, Vol. 18, No. 3, 2003, pp. 1196-1204. HUdoi:10.1109/TPWRS.2003.811170U
[3] D. J. Shin, j. O. Kim, T. K. Kim, J. B. Choo and C. Singh, “Optimal Service Restoration and Reconfiguration of Network Using Genetic-Tabu Algorithm,” Electrical Power Systems Research, Vol. 71, No. 2, 2004, pp. 145-152. HUdoi:10.1016/j.epsr.2004.01.016U
[4] B. Venkatesh, R. Ranjan and H. B. Gooi, “Optimal Reconfiguration of Radial Distribution Systems to Maximize Loadability,” IEEE Transactions On Power Systems, Vol. 19, No. 1, 2004, pp. 260-266. HUdoi:10.1109/TPWRS.2003.818739U
[5] R. Ranjan, B. Venkateshand and D. Das, “Optimal Conductor Selection of Radial Distribution Networks Using Fuzzy Adaptation of Evolutionary Programming,” International Journal of Power and Energy systems, Vol. 26, No. 3, 2006, pp. 401-416. HUdoi:10.2316/Journal.203.2006.3.203-3444U
[6] P. V. V. Rama Rao and S. Sivanagaraju, “Radial Distribution Network Reconfiguration for Loss Reduction and Load Balancing Using Plant Growth Simulation Algorithm,” International Journal on Electrical Engineering and Informatics, Vol. 2, No. 4, 2010, pp. 266-277.
[7] M. S. Thomas, R. Ranjan and R. Raina, “Fuzzy Modeled Load Flow Solution for Unbalanced Radialpower Distribution System,” Proceedings of the IASTED International Conference on Power and Energy Systems (EuroPES 2011), Crete, 22-24 June 2011, pp. 153-159.
[8] N. C. Sahoo and K. Prasad, “A Fuzzy Genetic Approach for Network Reconfiguration to Enhance Voltage Stability in Radial Distribution Systems,” Energy Conversion and Management, Vol. 47, No. 18-19, 2006, pp. 3288- 3306. HUdoi:10.1016/j.enconman.2006.01.004U
[9] D. Thukram, H. M. W. Banda and J. Jerome, “A Robust Three Phase Power Flow Algorithm for Radial Distribution Systems,” Journal of Electrical Power Systems Research, Vol. 50, No. 3, 1999, pp. 227-236. HUdoi:10.1016/S0378-7796(98)00150-3U

  
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