Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

Maximising energy capture from distributed generators in weak networks

Maximising energy capture from distributed generators in weak networks

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IEE Proceedings - Generation, Transmission and Distribution — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

The paper discusses the implications of the increasing capacity of synchronous generators at the remote ends of rural distribution networks where the line resistances are high and the X/R ratios are low. Local voltage variation is specifically examined and two methods of compensation are proposed. The first of them is a deterministic system that uses a set of rules to switch intelligently between voltage and power factor control modes, while the second is based on a fuzzy inference system that adjusts the reference setting of the automatic power factor controller in response to the terminal voltage. Extensive simulations have verified that the proposed approaches may increase the export of real power while maintaining voltage within the statutory limits.

References

    1. 1)
      • T. Takagi , M. Sugeno . Fuzzy identification of systems and its application to modelling and control. IEEE Trans. Syst. Man. Cybern. , 116 - 132
    2. 2)
      • Wallace, A.R.: `Protection of embedded generation schemes', IEE Colloq. on Protection and Connection of Renewable Energy Systems, 9 November 1999, p. 1/1–1/5.
    3. 3)
      • Y.-H. Song , A.T. Johns . Applications of fuzzy logic in power systems, Part 1. Power Eng. J. , 5 , 219 - 222
    4. 4)
      • `Recommended practice for excitation systtem models for power system stability studies', IEEE Standard 421.5-1992, August 1992.
    5. 5)
      • `Impact of renewable generation on the electrical transmission network in Scotland', October 2001.
    6. 6)
      • J.J. Grainger , W.D. Stevenson . (1994) Power system analysis.
    7. 7)
      • Wallace, A.R., Kiprakis, A.E.: `Reduction of voltage violations from embedded generators connected to the distribution network by intelligent reactive power control', Proc. 5th Int. Conf. on Power System Management and Control, 2001, p. 210–215.
    8. 8)
      • G.P. Harrison , A.E. Kiprakis , A.R. Wallace . Network integration of mini-hydro generation in liberalised markets. Int. Water Power Dam Constr. , 11 , 20 - 24
    9. 9)
      • W. Pedrycz . (1989) Fuzzy control and fuzzy systems.
    10. 10)
      • C.L. Masters . Voltage rise: the big issue when connecting embedded generation to long 11 kv overhead lines. Power Eng. J. , 1 , 5 - 12
    11. 11)
      • H. Ying . Constructing nonlinear variable gain controllers via the takagi-sugeno fuzzy control. IEEE Trans. Fuzzy Sys. , 2 , 226 - 234
http://iet.metastore.ingenta.com/content/journals/10.1049/ip-gtd_20040697
Loading

Related content

content/journals/10.1049/ip-gtd_20040697
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address