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International Journal of Photoenergy
Volume 2014, Article ID 704839, 10 pages
Research Article

Enhanced Particle Swarm Optimization-Based Feeder Reconfiguration Considering Uncertain Large Photovoltaic Powers and Demands

1Department of Electrical Engineering, Chung Yuan Christian University, Chungli City 320, Taiwan
2Department of Electrical Engineering, National Central University, Chungli City 320, Taiwan

Received 19 February 2014; Accepted 8 April 2014; Published 30 April 2014

Academic Editor: Ching-Song Jwo

Copyright © 2014 Ying-Yi Hong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [3 citations]

The following is the list of published articles that have cited the current article.

  • Antonino Laudani, Gabriele Maria Lozito, Francesco Riganti Fulginei, and Alessandro Salvini, “Hybrid Neural Network Approach Based Tool for the Modelling of Photovoltaic Panels,” International Journal of Photoenergy, vol. 2015, pp. 1–10, 2015. View at Publisher · View at Google Scholar
  • Dawit Fekadu Teshome, and Kuo Lung Lian, “A smart distribution system reconfiguration algorithm with optimal active power scheduling considering various types of distributed generators,” IEEJ Transactions on Electrical and Electronic Engineering, 2016. View at Publisher · View at Google Scholar
  • Chidanandappa, and Ananthapadmanabha, “An Integrated Gravitational Search multi-objective algorithm for Distribution Network feeder reconfiguration with DGs,” International Conference on Electrical, Electronics, and Optimization Techniques, ICEEOT 2016, pp. 1973–1979, 2016. View at Publisher · View at Google Scholar