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All issues Volume 143 (2020) E3S Web Conf., 143 (2020) 02039 References
Open Access
Issue
E3S Web Conf.
Volume 143, 2020
2nd International Symposium on Architecture Research Frontiers and Ecological Environment (ARFEE 2019)
Article Number 02039
Number of page(s) 8
Section Environmental Science and Energy Engineering
DOI https://doi.org/10.1051/e3sconf/202014302039
Published online 24 January 2020
  1. M. Mosbah, S. Arif, R. D. Mohammedi and A. Hellal, “Optimum dynamic distribution network reconfiguration using minimum spanning tree algorithm, “ 2017 5th International Conference on Electrical Engineering-Boumerdes (ICEE-B), Boumerdes, 2017, pp. 1-6. [Google Scholar]
  2. Y. Liu, J. Li and L. Wu, “Coordinated Optimal Network Reconfiguration and Voltage Regulator/DER Control for Unbalanced Distribution Systems, “ in IEEE Transactions on Smart Grid, vol. 10, no. 3, pp. 2912-2922, May 2019. [Google Scholar]
  3. X. Bai, Y. Mavrocostanti, D. Strickland and C. Harrap, “Distribution network reconfiguration validation with uncertain loads-network configuration determination and application, “ in IET Generation, Transmission & Distribution, vol. 10, no. 12, pp. 2852-2860, 2 9 2016. [CrossRef] [Google Scholar]
  4. M. Amin Heidari, “Optimal network reconfiguration in distribution system for loss reduction and voltageprofile improvement using hybrid algorithm of PSO and ACO, “ in CIRED-Open Access Proceedings Journal, vol. 2017, no. 1, pp. 2458-2461, 10 2017. [CrossRef] [Google Scholar]
  5. C. Lee, C. Liu, S. Mehrotra and Z. Bie, “Robust Distribution Network Reconfiguration, “ in IEEE Transactions on Smart Grid, vol. 6, no. 2, pp. 836-842, March 2015. [Google Scholar]
  6. P. Gangwar, S. N. Singh and S. Chakrabarti, “Network reconfiguration for unbalanced distribution systems, “ TENCON 2017-2017 IEEE Region 10 Conference, Penang, 2017, pp. 3028-3032. [Google Scholar]
  7. S. Ahmadi and S. Abdi, “Optimal reconfiguration of unbalanced distribution systems using a new hybrid Big Bang-Big Crunch algorithm for loss reduction, “ 2015 20th Conference on Electrical Power Distribution Networks Conference (EPDC), Zahedan, 2015, pp. 53-59. [Google Scholar]
  8. A. Tyagi, A. Verma and P. R. Bijwe, “Reconfiguration of balanced and unbalanced distribution systems for cost minimization, “ TENCON 2017-2017 IEEE Region 10 Conference, Penang, 2017, pp. 2188-2192. [Google Scholar]
  9. D. Sosic and P. Stefanov, “Reconfiguration of the three phase unbalanced distribution network, “ Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MedPower 2016), Belgrade, 2016, pp. 1-8. [Google Scholar]
  10. F. Capitanescu, L. F. Ochoa, H. Margossian and N. D. Hatziargyriou, “Assessing the Potential of Network Reconfiguration to Improve Distributed Generation Hosting Capacity in Active Distribution Systems, “ in IEEE Transactions on Power Systems, vol. 30, no. 1, pp. 346-356, Jan. 2015. [CrossRef] [Google Scholar]
  11. J. Wen, Y. Tan, L. Jiang and K. Lei, “Dynamic reconfiguration of distribution networks considering the real-time topology variation, “ in IET Generation, Transmission & Distribution, vol. 12, no. 7, pp. 1509-1517, 10 4 2018. [CrossRef] [Google Scholar]
  12. S. R. Tuladhar, J. G. Singh and W. Ongsakul, “Multi-objective approach for distribution network reconfiguration with optimal DG power factor using NSPSO, “ in IET Generation, Transmission & Distribution, vol. 10, no. 12, pp. 2842-2851, 2 9 2016. [CrossRef] [Google Scholar]
  13. L. Xu, R. Cheng, Z. He, J. Xiao and H. Luo, “Dynamic Reconfiguration of Distribution Network Containing Distributed Generation, “ 2016 9th International Symposium on Computational Intelligence and Design (ISCID), Hangzhou, 2016, pp. 3-7. [Google Scholar]
  14. G. Canzhi, B. Zhejing and Y. Wenjun, “Dynamic reconfiguration of distribution network with PV generation prediction based on credibility theory, “ 2016 Chinese Control and Decision Conference (CCDC), Yinchuan, 2016, pp. 1224-1229. [Google Scholar]
  15. D. Das, “A fuzzy multiobjective approach for network reconfiguration of distribution systems, “ in IEEE Transactions on Power Delivery, vol. 21, no. 1, pp. 202-209, Jan. 2006. [CrossRef] [Google Scholar]
  16. Zhang, Peng, W. Li, and S. Wang, “Reliabilityoriented distribution network reconfiguration considering uncertainties of data by interval analysis.” in International Journal of Electrical Power & Energy Systems, 34.1(2012):138-144. [CrossRef] [Google Scholar]
  17. R. Hasanpour, B. M. Kalesar, J. B. Noshahr and P. Farhadi, “Reconfiguration of smart distribution network considering variation of load and local renewable generation, “ 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), Milan, 2017, pp. 1-5. [Google Scholar]
  18. H. Wu, P. Dong and M. Liu, “Distribution Network Reconfiguration for Loss Reduction and Voltage Stability with Random Fuzzy Uncertainties of Renewable Energy Generation and Load, “ in IEEE Transactions on Industrial Informatics. [Google Scholar]
  19. H. Wu and P. Dong, “PPSO method for distribution network reconfiguration considering the stochastic uncertainty of wind turbine, photovoltaic and load, “ in The Journal of Engineering, vol. 2017, no. 13, pp. 2032-2036, 2017. [CrossRef] [Google Scholar]
  20. Y. Liu, J. Li and L. Wu, “Distribution System Restructuring: Distribution LMP via Unbalanced ACOPF, “ in IEEE Transactions on Smart Grid, vol. 9, no. 5, pp. 4038-4048, Sept. 2018. [Google Scholar]
  21. Kendall M. Kendall’s Advanced Theory of Statistics. New York (NY, USA): Oxford University Press, 1987. [Google Scholar]
  22. Pei Zhang and S. T. Lee, “Probabilistic load flow computation using the method of combined cumulants and Gram-Charlier expansion, “ in IEEE Transactions on Power Systems, vol. 19, no. 1, pp. 676-682, Feb. 2004. [CrossRef] [Google Scholar]
  23. S. Zhang, H. Cheng, L. Zhang, M. Bazargan and L. Yao, “Probabilistic Evaluation of Available Load Supply Capability for Distribution System, “ in IEEE Transactions on Power Systems, vol. 28, no. 3, pp. 3215-3225, Aug. 2013. [CrossRef] [Google Scholar]
  24. P. Wei, J. Liu, Q. Zhou and D. Wang, “A probabilistic power flow algorithm based on semivariable and series expansion, “ 2017 IEEE 2nd International Conference on Big Data Analysis (ICBDA), Beijing, 2017, pp. 563-567. [Google Scholar]
  25. Peng, Chunhua, et al. “Dynamic economic dispatch for wind-thermal power system using a novel bipopulation chaotic differential evolution algorithm, “ in International Journal of Electrical Power&Energy Systems, vol. 42, no. 1, pp. 119-126, 2012. [CrossRef] [Google Scholar]

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