Paper Titles
The Design Study on a Novel MW Wind Power Generation Speed-Up Machine
p.697
Optimization of Smoothing Control in Hybrid Wind and Battery Energy Storage System
p.703
An Improved Newton's Method and its Application in Power System
p.708
Multi-Objective Programming and Time Optimal Algorithm Research
p.715
Optimal Planning of Distributed Generation Using Self-Organizing Optimization Algorithm
p.720
Design and Analysis of High Availability Power Grid Dispatching Automation System Based on Virtualization Technology
p.725
Optimization of Parameters of Aircraft Landing Gear with Orthogonal Turn-Milling Based on GRA-PSO Algorithm
p.730
The Application Base on Frame Optimization Method in the Rectangular Hole Group Position Error
p.735
The Analysis of Circuit Breaker Health Index and the Characteristic Quantity
p.740

Optimal Planning of Distributed Generation Using Self-Organizing Optimization Algorithm

Article Preview

Abstract:

Recently, distributed generation (DG) has gained lots of attention due to a variety of benefits it can bring to the traditional power produce and distribution system. Identify the optimal location and size of DG in the distribution network is one of the crucial problems of DG integration, because a non-optimal planning might cause some adverse effects. In this paper, an optimization model with the consideration of minimizing energy losses is formulated first, and then an optimization methodology based on the Self-organizing Optimization Algorithm (SOA) is proposed. Finally, a case study is carried out to demonstrate the effectiveness of the proposed procedure.

You might also be interested in these eBooks
Material Science and Advanced Technologies in Manufacturing View Preview

Info:

Periodical:

Advanced Materials Research (Volume 852)

Pages:

720-724

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.852.720

Citation:

Cite this paper

Online since:

January 2014

Authors:

Wen Song, Qi Qiang Li

Keywords:

Distributed Generation (DG), Distribution Network Planning, Line Loss Minimization, Self-Organizing Optimization Algorithm

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

References

[1] R. Viral, and D. K. Khatod, Optimal planning of distributed generation systems in distribution system: A review, Renewable and Sustainable Energy Reviews, vol. 16, no. 7, pp.5146-5165, (2012).

DOI: 10.1016/j.rser.2012.05.020

Google Scholar

[2] G. Celli, S. Mocci, F. Pilo, and G. G. Soma, A Multi-Objective Approach for the Optimal Distributed Generation Allocation with Environmental Constraints, " in Probabilistic Methods Applied to Power Systems, 2008. PMAPS , 08. Proceedings of the 10th International Conference on, 2008, pp.1-8.

DOI: 10.1109/pmaps.2006.360270

Google Scholar

[3] G. Celli, E. Ghiani, S. Mocci, and F. Pilo, A multiobjective evolutionary algorithm for the sizing and siting of distributed generation, Power Systems, IEEE Transactions on, vol. 20, no. 2, pp.750-757, (2005).

DOI: 10.1109/tpwrs.2005.846219

Google Scholar

[4] S. Abdi, and K. Afshar, Application of IPSO-Monte Carlo for optimal distributed generation allocation and sizing, International Journal of Electrical Power & Energy Systems, vol. 44, no. 1, pp.786-797, (2013).

DOI: 10.1016/j.ijepes.2012.08.006

Google Scholar

[5] Y. Wen-rong, W. U. Hai-yan, L. I. Lian-bing, and W. Hua-jun, Planning of distribution network with DG based on artificial fish swarm algorithm, Power System Protection and Control, vol. 38, no. 21, pp.156-161, (2010).

Google Scholar

[6] S. Boettcher, and A. G. Percus, Extremal optimization: Methods derived from co-evolution, in Proc of the Genetic and Evolutionary Computation Conf, San Francisco, 1999, pp.825-832.

Google Scholar

[7] Z. Yong, Y. Jing-yan, and Z. Dong-qing, Planning of distributed generation based on optimal real power losses, Power System Protection and Control, vol. v. 39; No. 351, no. 21, pp.12-16, (2011).

Google Scholar