Call for Paper - January 2024 Edition
IJCA solicits original research papers for the January 2024 Edition. Last date of manuscript submission is December 20, 2023. Read More

Placement and Sizing of Distributed Generation on Distribution Systems with a Multi-Objective Particle Swarm Optimization and Analytical Approach: A Review

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Pooja Shivwanshi, Sameena Elias Mubeen

Pooja Shivwanshi and Sameena Elias Mubeen. Placement and Sizing of Distributed Generation on Distribution Systems with a Multi-Objective Particle Swarm Optimization and Analytical Approach: A Review. International Journal of Computer Applications 161(12):21-24, March 2017. BibTeX

	author = {Pooja Shivwanshi and Sameena Elias Mubeen},
	title = {Placement and Sizing of Distributed Generation on Distribution Systems with a Multi-Objective Particle Swarm Optimization and Analytical Approach: A Review},
	journal = {International Journal of Computer Applications},
	issue_date = {March 2017},
	volume = {161},
	number = {12},
	month = {Mar},
	year = {2017},
	issn = {0975-8887},
	pages = {21-24},
	numpages = {4},
	url = {},
	doi = {10.5120/ijca2017913111},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


The Distributed generations (DGs) have number of benefits in the electric power industry, such as improvement of voltage stability, enhancement of reliability and power quality. This paper compares the DG placement result of analytical approach with the Multi-Objective Particle Swarm Optimization (MOPSO). The analytical method is based on a formulation for the power flow problem. A priority is loss sensitivity to determine the best locations of applicant distributed generation units. The multi-objective particle swarm optimization determines the optimal DGs places and sizes. The MOPSO improves voltage profile and stability, power-loss reduction, and reliability enhancement. The results show that the analytical method could lead to optimal or near-optimal result, while requiring lower computational effort.


  1. D. Q. Hung, N. Mithulananthan, and R. C. Bansal, "Analytical Expressions for DG Allocation in Primary Distribution Networks," IEEE Trans. on Energy Conversion, vol. 25, no. 3, Sept. 2010, pp. 814-820.
  2. S. Civanlar, J. J. Grainger, H. Yin, and S. S. H. Lee, “Distribution feeder reconfiguration for loss reduction,” IEEE Trans. Power Del., vol. 3, no. 3, pp. 1217–1223, Jul. 1988.
  3. N. Acharya, P. Mahat, and N. Mithulananthan, “An analytical approach for DG allocation in primary distribution network,” Int. J. Electr. Power Energy Syst., vol. 28, no. 10, pp. 669–678, 2006.
  4. M. El-Arini and A. Fathy, "An Efficient and reliable method for optimal allocating of the distributed generation based on optimal teaching learning algorithm," WSEAS Trans. on Power Systems, vol. 10, 2015, pp. 188-197.
  5. S. Kansal, V. Kumar, and B. Tyagi, "Hybrid Approach for Placement of Type-III Multiple DGs in Distribution Network," J. Electrical & Electronic Systems, 2014, 3:130
  6. R. Rao, K. Ravindra, K. Satish, S. Narasimham, ‘Power loss minimization in distribution system using network reconfiguration in the presence of distributed generation’, IEEE Trans. Power Syst., 2012, 28, (1), pp. 1–9
  7. T. Ackermann, G. Andersson, L. Soder, “Distributed generation: a definition,” Electr. Power Syst. Res., 2001, 57, pp. 195–204
  8. W. Caisheng and M. H. Nehrir, “Analytical approaches for optimal placement of distributed generation sources in power systems,” IEEE Trans. Power Syst., vol. 19, no. 4, pp. 2068–2076, Nov. 2004.
  9. M. A. Kashem, A. D. T. Le, M. Negnevitsky, and G. Ledwich, “Distributed generation for minimization of power losses in distribution systems,” presented at the Power Energy Soc. Gen. Meeting Conf., Montreal, QC, Canada, 2006.
  10. T. Ackermann, G. Anderson, and L. S. Soder, “Distributed generation: Adefinition,” Elect. Power Syst. Res., vol. 57, no. 3, pp. 195–204, 2011.
  11. M.M. Aman, G. B. Jasmon, H. Mokhlis, and A. H. A. Bakar, “Optimal placement and sizing of a DG based on a new power stability index and line losses,” Int. J. Elect. Power Energy Syst., vol. 43, no. 1, pp. 1296–1304, 2012.
  12. M. H. Moradi and M. Abedini, “A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems,” Int. J. Elect. Power Energy Syst., vol. 34, no. 7, pp. 66–74, 2006.
  13. S. Elsaiah, M. Benidris, J. Mitra, "Analytical approach for placement and sizing of distributed generation on distribution systems,"IET Gener. Transm. Distrib., 2014, Vol. 8, Iss. 6, pp. 1039–1049
  14. A. Ameli, S. Bahrami, F. Khazaeli and M.-Reza Haghifam, “A Multiobjective Particle Swarm Optimization for Sizing and Placement of DGs from DG Owner’s and Distribution Company’s Viewpoints” IEEE Trans. on Power Delivery, vol. 29, no. 4, Aug. 2014.


DG placement, DG sizing, distributed generation, Analytical optimization method, multiobjective particle swarm optimization (MOPSO).