Comparative study of Pareto optimal multi objective cuckoo search algorithm and multi objective particle swarm optimization for power loss minimization incorporating UPFC-Reference-Cited by-同舟云学术

Comparative study of Pareto optimal multi objective cuckoo search algorithm and multi objective particle swarm optimization for power loss minimization incorporating UPFC

Published:2020-05-28 Issue:1 Volume:12 Page:1069-1080
ISSN:1868-5137
Container-title:Journal of Ambient Intelligence and Humanized Computing
language:en
Short-container-title:J Ambient Intell Human Comput

Author:

Rao Nartu Tejeswara,Sankar Matta Mani^ORCID,Rao Surapu Prasada,Rao Boddepalli Srinivasa

Publisher

Springer Science and Business Media LLC

Subject

General Computer Science

Link

https://link.springer.com/content/pdf/10.1007/s12652-020-02142-4.pdf

Reference22 articles.

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2. Dutta S, Roy PK, Nandi D (2015) Optimal location of UPFC controller in transmission network using hybrid chemical reaction optimization algorithm. Int J Electr Power Energy Syst 64:194–211

3. Galiana FD, Almeida K, Toussaint M, Griffin J (1996) Assessment and control of the impact of FACTS devices on power system performance. IEEE Trans Power Syst 11(4):1931–1936

4. Gyugyi L, Schauder CD, Williams SL, Rietman TR, Torgerson DR, Edris A (1995) The unified power flow controller: a new approach to power transmission control. IEEE Trans Power Deliver 10(2):1085–1097

5. Hingorani NG, Gyugyi L (2000) Understanding FACTS: concepts and technology of flexible AC transmission Systems. IEEE Press, New York

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