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All issues Volume 38 (2016) MATEC Web of Conferences, 38 (2016) 01007 References
Open Access
Issue
MATEC Web of Conferences
Volume 38, 2016
UTP-UMP Symposium on Energy Systems 2015 (SES 2015)
Article Number 01007
Number of page(s) 5
Section Thermal Engineering & Energy Conversion
DOI https://doi.org/10.1051/matecconf/20163801007
Published online 11 January 2016
  1. J. Federico, V. Gonzalez, and C. Lyra, “Learning classifiers shape reactive power to decrease losses in power distribution networks,” in Power Engineering Society General Meeting, 2005. IEEE, pp. 557–562 (2005). [Google Scholar]
  2. T. Ackermann, G. Andersson, and L. Söder, “Distributed generation: a definition,” Electric power systems research, vol. 57, pp. 195–204, (2001). [Google Scholar]
  3. M. Ettehadi, H. Ghasemi, and S. Vaez-Zadeh, “Voltage stability-based DG placement in distribution networks,” Power Delivery, IEEE Transactions on, vol. 28, pp. 171–178, (2013). [CrossRef] [Google Scholar]
  4. A. L’Abbate, G. Fulli, F. Starr, and S. D. Peteves, “Distributed Power Generation in Europe: technical issues for further integration,” Joint Research Center Institute for Energy. WWW.CaRBoNWaRRooM.CoM2007, (2007). [Google Scholar]
  5. S. Kalambe and G. Agnihotri, “Loss minimization techniques used in distribution network: bibliographical survey,” Renewable and Sustainable Energy Reviews, vol. 29, pp. 184–200, (2014). [CrossRef] [Google Scholar]
  6. J. D. G. Pepermans., D.Haeseldonckx, W. D’haeseleer, R. Belmans, “WORKING PAPER SERIES n°2003-8 (K.U.Leuven - Energy Institute)” (2003). [Google Scholar]
  7. N. Roy and H. Pota, “Current Status and Issues of Concern for the Integration of Distributed Generation Into Electricity Networks,” (2014). [Google Scholar]
  8. V. A. Evangelopoulos and P. S. Georgilakis, “Optimal distributed generation placement under uncertainties based on point estimate method embedded genetic algorithm,” IET Generation, Transmission & Distribution, vol. 8, pp. 389–400, (2014). [Google Scholar]
  9. M. Aman, G. Jasmon, A. Bakar, and H. Mokhlis, “A new approach for optimum simultaneous multi-DG distributed generation Units placement and sizing based on maximization of system loadability using HPSO (hybrid particle swarm optimization) algorithm,” Energy, vol. 66, pp. 202–215, (2014). [CrossRef] [Google Scholar]
  10. W.-S. Tan, M. Y. Hassan, M. S. Majid, and H. Abdul Rahman, “Optimal distributed renewable generation planning: A review of different approaches,” Renewable and Sustainable Energy Reviews, vol. 18, pp. 626–645, (2013). [CrossRef] [Google Scholar]
  11. R. Viral and D. Khatod, “Optimal planning of distributed generation systems in distribution system: A review,” Renewable and Sustainable Energy Reviews, vol. 16, pp. 5146–5165, (2012). [CrossRef] [Google Scholar]
  12. Y. Huang, “Electricity Distribution Network Planning Considering Distributed Generation,” PhD, KTH School of Electrical Engineering, KTH, SWEDEN, (2014). [Google Scholar]
  13. M. Aman, G. Jasmon, H. Mokhlis, and A. Bakar, “Optimal placement and sizing of a DG based on a new power stability index and line losses,” International Journal of Electrical Power & Energy Systems, vol. 43, pp. 1296–1304, (2012). [Google Scholar]
  14. P. Hallberg, “Active Distribution System Management a key tool for the smooth integration of distributed generation”, Eurelectric TF Active System Management, (2013). [Google Scholar]
  15. H. L. Willis, “Analytical methods and rules of thumb for modeling DG-distribution interaction,” in Power Engineering Society Summer Meeting, 2000. IEEE, pp. 1643–1644 (2000). [Google Scholar]
  16. C. Wang and M. H. Nehrir, “Analytical approaches for optimal placement of distributed generation sources in power systems,” Power Systems, IEEE Transactions on, vol. 19, pp. 2068–2076, (2004). [Google Scholar]
  17. N. Acharya, P. Mahat, and N. Mithulananthan, “An analytical approach for DG allocation in primary distribution network,” International Journal of Electrical Power & Energy Systems, vol. 28, pp. 669–678, (2006). [Google Scholar]
  18. D. Q. Hung, N. Mithulananthan, and R. Bansal, “Analytical expressions for DG allocation in primary distribution networks,” Energy Conversion, IEEE Transactions on, vol. 25, pp. 814–820, (2010). [Google Scholar]
  19. D. Q. Hung, N. Mithulananthan, and R. Bansal, “An optimal investment planning framework for multiple distributed generation units in industrial distribution systems,” Applied Energy, vol. 124, pp. 62–72, (2014). [CrossRef] [Google Scholar]
  20. P. S. Georgilakis and N. D. Hatziargyriou, “Optimal distributed generation placement in power distribution networks: Models, methods, and future research,” IEEE Trans. Power Syst, vol. 28, pp. 3420–3428, (2013). [Google Scholar]
  21. R. Al Abri, E. F. El-Saadany, and Y. M. Atwa, “Optimal placement and sizing method to improve the voltage stability margin in a distribution system using distributed generation,” Power Systems, IEEE Transactions on, vol. 28, pp. 326–334, (2013). [Google Scholar]
  22. T. Gözel and M. H. Hocaoglu, “An analytical method for the sizing and siting of distributed generators in radial systems,” Electric Power Systems Research, vol. 79, pp. 912–918, (2009). [Google Scholar]
  23. L. F.Ochoa, C. J.Dent, and G. P.Harrison, “Distribution network capacity assessment: Variable DG and active networks,” Power Systems, IEEE Transactions on, vol. 25, pp. 87–95, (2010). [Google Scholar]
  24. A. Kumar and W. Gao, “Optimal distributed generation location using mixed integer non-linear programming in hybrid electricity markets,” IET generation, transmission & distribution, vol. 4, pp. 281–298, (2010). [CrossRef] [Google Scholar]
  25. D. Singh and K. Verma, “Multiobjective optimization for DG planning with load models,” Power Systems, IEEE Transactions on, vol. 24, pp. 427–436, (2009). [Google Scholar]
  26. W. Sheng, K. Liu, Y. Liu, X. Meng, and Y. Li, “Optimal Placement and Sizing of Distributed Generation via an Improved Nondominated Sorting Genetic Algorithm II,” (2014). [Google Scholar]
  27. A. El-Zonkoly, “Optimal placement of multi-distributed generation units including different load models using particle swarm optimization,” Swarm and Evolutionary Computation, vol. 1, pp. 50–59, (2011). [CrossRef] [Google Scholar]
  28. M. Nayeripour, E. Mahboubi-Moghaddam, J. Aghaei, and A. Azizi-Vahed, “Multi-objective placement and sizing of DGs in distribution networks ensuring transient stability using hybrid evolutionary algorithm,” Renewable and Sustainable Energy Reviews, vol. 25, pp. 759–767, (2013). [Google Scholar]
  29. S. M. Sajjadi, M.-R. Haghifam, and J. Salehi, “Simultaneous placement of distributed generation and capacitors in distribution networks considering voltage stability index,” International Journal of Electrical Power & Energy Systems, vol. 46, pp. 366–375, (2013). [CrossRef] [Google Scholar]
  30. M. H. Moradi, A. Zeinalzadeh, Y. Mohammadi, and M. Abedini, “An efficient hybrid method for solving the optimal sitting and sizing problem of DG and shunt capacitor banks simultaneously based on imperialist competitive algorithm and genetic algorithm,” International Journal of Electrical Power & Energy Systems, vol. 54, pp. 101–111, (2014). [CrossRef] [Google Scholar]
  31. P. Kayal and C. Chanda, “Placement of wind and solar based DGs in distribution system for power loss minimization and voltage stability improvement,” International Journal of Electrical Power & Energy Systems, vol. 53, pp. 795–809, (2013). [CrossRef] [Google Scholar]
  32. S. Devi and M. Geethanjali, “Optimal location and sizing determination of Distributed Generation and DSTATCOM using Particle Swarm Optimization algorithm,” International Journal of Electrical Power & Energy Systems, vol. 62, pp. 562–570, (2014). [CrossRef] [Google Scholar]

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