Distance Measure Based Rules for Voltage Regulation with Loss Reduction
Y. Rosales Hernandez, T Hiyama
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DOI: 10.4236/jemaa.2009.12013   PDF    HTML     5,280 Downloads   9,272 Views   Citations

Abstract

This paper presents a rule-based technique to control the voltage in a power transmission network. Transformers with a tap changer installed in the system are selected by the proposed technique as control devices. For each bus under volt-age violation, the most effective control device is selected by using the minimum electric distance criteria. In order to demonstrate the efficiency of the method, several simulations were performed using an IEEE 30-bus network as a model system. The distance measure technique is compared with classic voltage regulation approach and a genetic algorithm based. The results obtained show the robustness of the proposed method.

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Y. Hernandez and T. Hiyama, "Distance Measure Based Rules for Voltage Regulation with Loss Reduction," Journal of Electromagnetic Analysis and Applications, Vol. 1 No. 2, 2009, pp. 85-91. doi: 10.4236/jemaa.2009.12013.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] T. Ananthapadmanabha, “Knowledge-based expert system for optimal reactive power control in distribution system,” International Journal of Electrical Power and Energy Systems, Vol. 18, pp. 27-31, January 1996.
[2] Y. T. Liu, Z. G. Peng, and X. Z. Qiu, “Optimal volt/var control in distribution systems,” International Journal of Electrical Power and Energy Systems, Vol. 24, pp. 271-276, May 2002.
[3] Y. Malachi and S. Singer, “A genetic algorithm for the corrective control of voltage and reactive power,” IEEE Transactions on Power Systems, Vol. 21, pp. 295-300, February 2006.
[4] B. Das and P. K. Verma, “Artificial neural network-based optimal capacitor switching in a distribution system,” Electric Power System Research, Vol. 60, pp. 55-62, June 2001.
[5] H. I. Hagenaars, J. Imura, and H. Nijneijer, “Approximate continuous-time optimal control in obstacle avoidance by time/space descrifization of non-convex state constraints,” Proceedings of 2004 IEEE Conference on Control Applications, pp. 878-883, 2004.
[6] K. Y. Lee and M. A. El-Sharkawi, “Modern heuristic optimization techniques: Theory and applications to power systems,” New Jersey: Wiley-IEEE Press, pp. 173, 2008.
[7] Y. Rosales and T. Hiyama, “A review of genetic algorithms implemented for voltage/var optimization problems in electric network systems,” submitted for publishing.
[8] MATPOWER, http://www.pserc.cornell.edu/matpower/.

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