Using Genetic Algorithm for Distributed Generation Allocation to Reduce Losses and Improve Voltage Profile

This paper presents a method for the optimal allocation of Distributed generation in distribution systems. In this paper, our aim would be optimal distributed generation allocation for voltage profile improvement and loss reduction in distribution network. Genetic Algorithm (GA) was used as the solving tool, which referring two determined aim; the problem is defined and objective function is introduced. Considering to fitness values sensitivity in genetic algorithm process, there is needed to apply load flow for decision-making. Load flow algorithm is combined appropriately with GA, till access to acceptable results of this operation. We used MATPOWER package for load flow algorithm and composed it with our Genetic Algorithm. The suggested method is programmed under MATLAB software and applied ETAP software for evaluating of results correctness. It was implemented on part of Tehran electricity distributing grid. The resulting operation of this method on some testing system is illuminated improvement of voltage profile and loss reduction indexes.

Authors:

• M. Sedighizadeh
• A. Rezazadeh

Keywords:

• Distributed Generation
• Allocation
• Voltage Profile
• losses
• Genetic Algorithm.

References:

[1] K. Nara, Y. Hayashi, K. Ikeda,and T. Ashizawa, "Application of tabu
search to optimal placement of distributed generators," in Proc.
2001IEEE Power Engineering Society Winter Meeting, pp. 918-923.
[2] T. K. A. Rahman, S. R. A. Rahim, and I. Musirin, "Optimal allocation
and sizing of embedded generators," in Proc. 2004 National Power and
Energy Conference, pp.288-294.
[3] G. Celli, and F. Pilo, "Optimal distributed generation allocation in MV
distribution networks," in Proc.2001 IEEE PICA Conference, pp. 81-86.
[4] W. El-Khattam, K. Bhattacharya, Y. Hegazy, and M. M. A. Salama,
"Optimal investment planning for distributed generation in a competitive
electricity market," IEEE Trans. Power Systems, vol. 19, pp. 1674-1684,
Aug.2004.
[5] W. El-Khattam, Y. G. Hegazy, and M. M. A. Salama, "An integrated
distributed generation optimization model for distribution system
planning," IEEE Trans. Power Systems, vol. 20, pp. 1158-1165, May
2005.
[6] M. Gandomkar,M. Vakilian,M. Ehsan, " A combination of genetic
algorithm and simulated annealing for optimal DG allocation in
distribution networks", CCECE/CCGEI, Saskatoon, May 2005 IEEE,
PP.645-648.
[7] A. Keane, and M. O'Malley, "Optimal allocation of embedded
generation on distribution networks," IEEE Trans. Power Systems, vol.
20, pp. 1640-1646, Aug. 2005.
[8] Distributed generation: a definition; Thomas Ackermann , Göran
Andersson, Lennart Söder; Electric Power Systems Research 57 (2001)
195-204; December 2000.