DocumentCode
176116
Title
Research of immune algorithms for reconfiguration of distribution network with distributed generations
Author
Cailian Gu ; Jianwei Ji ; Li Liu
Author_Institution
Coll. of Electr. Eng., Shenyang Inst. of Eng., Shenyang, China
fYear
2014
fDate
May 31 2014-June 2 2014
Firstpage
2156
Lastpage
2160
Abstract
The structure of traditional distribution network is changed from a single supply radial network to a more power ring network when grid is connected with distributed generations (DG), and island phenomenon occurs higher in the process of reconstruction, which becomes uncontrolled and high risk operation and increased the difficulty of distribution network reconstruction. The improved immune genetic algorithm introduced the principle of biological immune mechanism into standard genetic algorithm is put forward, the problem of genetic algorithm premature convergence in distribution network calculation is overcome, constraint conditions of preventing islanding phenomenon in the reconstructed model is added, encoding method based on the loop is used. The calculation results show that, in the case of a distributed power supply, the loss of network can be decreased and voltage quality is improved by using this method, what is the most that island phenomenon is avoided. IEEE33 node is an example to prove the feasibility of the method.
Keywords
distributed power generation; genetic algorithms; power distribution faults; power supply quality; IEEE 33 node system; biological immune mechanism; constraint conditions; distributed generation; distributed power supply; distribution network reconfiguration; encoding method; genetic algorithm; immune algorithm; island phenomenon; voltage quality; Encoding; Genetic algorithms; Heuristic algorithms; Immune system; Load flow; Optimization; DG; Distribution Reconfiguration; Immune genetic algorithm; Islanding phenomenon;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location
Changsha
Print_ISBN
978-1-4799-3707-3
Type
conf
DOI
10.1109/CCDC.2014.6852524
Filename
6852524
Link To Document