The Optimal Configuration of Feeder Switches in DAS Based on Pareto Optimality Solution

Article Preview

Abstract:

In urban radial networks, the feeder is often complex with a main line, branches and even sub-branches. It is necessary to optimize the configuration of automation switching devices in distribution automation system (DAS) to reduce the impact range of power outage and improve the power supply reliability. The interruption frequency and the space-time relationship among the switching devices were ignored in the most of researches. This paper presents a new reliability planning scheme of switching devices in DAS which involves three types of circuit breakers and three types of load switches. The model which target is to get the minimal cost, the lowest average annual interruption frequency and the least interruption duration is built thereby. The constraint is the availability rate of electricity supply of load node. Based on the Pareto optimality theory, the multi-objective differential evolution algorithm is adopted to solve the Pareto front efficiently. The proposed algorithm can provide many optional choices and the final scheme can be chosen based on the situation. Finally, a practical example is used to illustrate the developed scheme.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 1008-1009)

Pages:

461-465

Citation:

Online since:

August 2014

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Billinton R, Billinton J E. IEEE Transactions on Power Delivery, Vol. 4 (1989), p.561.

Google Scholar

[2] WANG Jing-tao, XIE Kai-gui, CAO Kan, FENG Yi., Power System Technology, Vol. 32, (2008), p.47.

Google Scholar

[3] WAN Guo-cheng, GUO Xiaoyu, REN Zhen, Relay, Vol. 30 (2005), p.10, in Chinese.

Google Scholar

[4] XU Dan, TANG Wei, Power System Protection and Control, Vol. 37 (2009), p.47, in Chinese.

Google Scholar

[5] Mei Mingwei, Zhang Quanqi. SHANDONG DIANLI JISHU, Vol. 197(2014), p.54, in Chinese.

Google Scholar

[6] I. Lim, T. S. Sidhu, M. S. Choi, S. J. Lee B.N. Ha. IEEE Trans on Power Delivery, vol28 (2013), p.1474.

Google Scholar

[7] H.A.Abbass,R.Sarker, International Journal on Artificial Intelligence Tools, Vol. 11 (2002), p.531.

Google Scholar