DocumentCode :
2642384
Title :
Application of intelligent algorithm in island detection of distributed generation
Author :
Lin, Xia ; Dong, Xiaofeng ; Lu, Yuping
Author_Institution :
Sch. of Electr. Eng., Hohai Univ., Nanjing, China
fYear :
2010
fDate :
19-22 April 2010
Firstpage :
1
Lastpage :
7
Abstract :
In the grid-connection, the distributed generation system in the status of the islanding is liable for damage to equipment, affecting the performance of the utility. Seriously, island may create a hazard for utility line-worker. Islanding detection methods for distributed generation system are reviewed. Characterized by high efficiency and performance, C4.5 decision-tree is particularly applicable to the condition of large amounts of mining data. The paper proposes a new approach based on C4.5 decision-tree for islanding detection in distributed generation system. Without any negative effect on the power quality, this novel method greatly reduces the damage to the utility resulting from the islanding running state, and also highly enhances the capability of detecting islands of the protection relay. How to construct C4.5 decision-tree on the basis of past operation data of an existed distributed generation system was introduced in detail firstly. And this method was tested on a typical distribution system with multiple distributed recourses by using Matlab/Simulink tools. The simulation results show that C4.5 decision-tree is effective and the island operating mode of DGs can be totally forecasted by this new algorithm.
Keywords :
Data mining; Distributed control; Hazards; Inverters; Power quality; Power system protection; Power systems; Predictive models; Relays; Renewable energy resources; C4.5; Data Mining; Distributed Generation; Islanding Detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Transmission and Distribution Conference and Exposition, 2010 IEEE PES
Conference_Location :
New Orleans, LA, USA
Print_ISBN :
978-1-4244-6546-0
Type :
conf
DOI :
10.1109/TDC.2010.5484724
Filename :
5484724
Link To Document :
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