Skip to main content
SpringerLink
Log in
Book cover

International Conference on Electrical and Information Technologies for Rail Transportation

EITRT 2017: Proceedings of the 3rd International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2017 pp 79–87Cite as

Distribution Network Planning Considering DG Under Uncertainty

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 482))

Abstract

With the rise of a new round of energy revolution, the distribution network with distributed generation (DG) has become an important form of the future power grid. However, DG itself has the characteristics of randomness and intermittence, which brings impacts and challenges to the distribution network planning. Based on the uncertainty theory, the fuzzy simulation of DG and load are used to model the distribution network. The model takes the minimum annual investment cost and the minimum cost of network loss as the optimization target. Single parent genetic algorithm based on spanning tree is optimized and verified by 18 node system simulation.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover 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

References

  1. Zhao MA, Ting AN, Yuwei S (2016) State of the art and development trends of power distribution technologies. Proc CSEE 36(6):1552–1567

    Google Scholar 

  2. Zhang LM, Tang W, Zhao Y et al (2010) The integrated evaluation of impact of distributed generation on distribution network. Power Syst Protect Control 38(21):132–135, 140

    Google Scholar 

  3. Fuchun H, Mingkai Z (1994) Research on urban power network planning. Autom Electr Power Syst 18(11):57–62

    Google Scholar 

  4. Weidong T (1993) New development of foreign power planning. Energy of China 1(6–9):25

    Google Scholar 

  5. Zhang W, Cheng H, Cheng Z (2008) Review of distribution network optimal planning. Autom Electr Power Syst 20(5):16–23 (in Chinese)

    Google Scholar 

  6. De Figueiredo LH, Stolfi J (2004) Affine arithmetic: concepts and applications. Numer Algorithms 37(1):147–158

    Article  MathSciNet  MATH  Google Scholar 

  7. Tang N (2015) A study on the expansion planning of distribution systems considering distributed generations. Beijing Jiaotong University

    Google Scholar 

  8. Zhang H (2015) Dynamic optimal dispatch of active distribution network with electric vehicle aggregators. School of Electrical and Electronic Engineering

    Google Scholar 

  9. Liu BD, Zhao RQ, Wang G (2003) Uncertain programming with applications. Tsinghua University Press, Beijing

    Google Scholar 

  10. Karaki SH, Chedid RB, Ramadan R (1999) Probabilistic performance assessment of autonomous solar-wind energy conversion systems. IEEE Trans Energy Convers 14(3):766–772

    Article  Google Scholar 

  11. Abouzahr I, Ramakumar R (1991) Loss of power supply probability of stand-alone photovoltaic systems: a closed form solution approach. IEEE Trans Energy Convers 6(1):1–11

    Article  Google Scholar 

  12. Maojun L (2002) Theory and application of partheno genetic algorithm. Hunan University

    Google Scholar 

  13. Wang X (1990) Optimal planning of power system. China Water Power Press, Beijing

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Electrical Engineering, Beijing Jiaotong University, No. 3 Shang Yuan Cun, Haidian District, Beijing, China

    Yanfei Liu & Hui Zhou

Authors
  1. Yanfei Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hui Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yanfei Liu .

Editor information

Editors and Affiliations

  1. School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China

    Limin Jia

  2. Beijing Jiaotong University, Beijing, China

    Yong Qin

  3. CRRC Zhuzhou Locomotive Co., Ltd., Zhuzhou, China

    Jianguo Suo

  4. CRRC Zhuzhou Institute Co., Ltd., Zhuzhou, China

    Jianghua Feng

  5. Beijing Jiaotong University, Beijing, China

    Lijun Diao

  6. University of Salford, Manchester, United Kingdom

    Min An

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Liu, Y., Zhou, H. (2018). Distribution Network Planning Considering DG Under Uncertainty. In: Jia, L., Qin, Y., Suo, J., Feng, J., Diao, L., An, M. (eds) Proceedings of the 3rd International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2017. EITRT 2017. Lecture Notes in Electrical Engineering, vol 482. Springer, Singapore. https://doi.org/10.1007/978-981-10-7986-3_9

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-7986-3_9

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7985-6

  • Online ISBN: 978-981-10-7986-3

  • eBook Packages: EnergyEnergy (R0)

Publish with us

Policies and ethics

Search

Navigation