Skip to main content

Network Reconfiguration at the Distribution System with Distributed Generators

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6329))

Abstract

This article proposes a novel model for distribution network reconfiguration to meet current distribution system operating demands. In the model the connection of distributed generators to distribution system is considered, and from the view of the actual operation demands, operating modes are proposed to simulate the load changes and DG fluctuations and can be used to achieve the aim that the network reconfigures only once in a period. Then the binary particle swarm optimization algorithm with dynamic adaptation of inertia weight has been applied to solve the model. A typical example proved the feasibility and validity of the model and the algorithm.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Liu, W., Han, Z.X.: Distribution network reconfiguration based on optimal flow pattern algorithm and genetic algorithm. Power System Technology 28, 29–33 (2004)

    Google Scholar 

  2. Zhang, D., Zhang, L.C., Fu, Z.G.: A Quick Branch-exchange Algorithm for Reconfigurationof Distribution Networks. Power System Technology 29, 82–85 (2005)

    Google Scholar 

  3. Yu, Y.X., Duan, G.: Shortest Path Algorithm and Genetic Algorithm Based Distribution System Reconfiguration. Proceedings of the CSEE 20, 44–49 (2000)

    Google Scholar 

  4. Hu, M.X., Chen, Y.: Simulated annealing algorithm of optimal reconfiguration in distribution system. Automation of Electric Power Systems 18, 24–28 (1994)

    Google Scholar 

  5. Kashem, M.A., Jasmon, G.B., et al.: Artificial neural network approach to network reconfiguration for loss minimization in distribution networks. Electrical Power &Energy Systems 20, 247–258 (1998)

    Article  Google Scholar 

  6. Yuan, X.H., Wang, C., Zhang, Y.C., et al.: A survey on application of particle swarm optimization to electric power systems. Power System Technology 28, 14–19 (2004)

    Google Scholar 

  7. Bai, D.D., Liu, G.Q., Guo, L.: Distribution network reconfiguration based on improved particle swarm optimization algorithm. Journal of North China Electric Power University 33, 20–23 (2006)

    Google Scholar 

  8. Liu, D.P., Ma, B., Li, R.Y., Chen, Z.H.: Current situation and prospects of distributed generation technologies. Energy Research and Information 18, 1–9 (2002)

    Google Scholar 

  9. Jin, X.L., Zhao, J.G.: Distribution Network Reconfiguration for Load Balancing Based on Improved Binary Particle Swarm Optimization Algorithm. Power System Technology 29, 40–43 (2005)

    Google Scholar 

  10. Shi, Y., Eberhart, R.: A modified particle swarm optimizer. In: IEEE International Conference of Evolutionary Computation, Anchorage, Alaska (1998)

    Google Scholar 

  11. Zhang, L.P., Yu, H.J., Chen, D.Z.: Analysis and Improvement of Particle Swarm Optimization Algorithm. Information and Control 33, 513–571 (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Xiaozhi, G., Linchuan, L., Hailong, X. (2010). Network Reconfiguration at the Distribution System with Distributed Generators. In: Li, K., Fei, M., Jia, L., Irwin, G.W. (eds) Life System Modeling and Intelligent Computing. ICSEE LSMS 2010 2010. Lecture Notes in Computer Science, vol 6329. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15597-0_44

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-15597-0_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15596-3

  • Online ISBN: 978-3-642-15597-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics