Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/27564
Title: An intelligent dynamic security assessment framework for power systems with wind power
Authors: Xu, Y
Dong, ZY
Xu, Z 
Meng, K
Wong, KP
Keywords: Dynamic security assessment
Extreme learning machine
Intelligent system
Soft computing
Wind power
Issue Date: 2012
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on industrial informatics, 2012, v. 8, no. 4, 6227533, p. 995-1003 How to cite?
Journal: IEEE transactions on industrial informatics 
Abstract: The increasing penetration of wind power can alter the dynamic security characteristic of a power system. To accommodate rapid and volatile wind power variations, dynamic security assessment (DSA) against foreseeable disturbances is required to be carried out online and provide security monitoring results within sufficiently small time frame. Based on soft computing (SC) technologies, this paper develops an intelligent framework for real-time DSA of power systems with large penetration of wind power. It consists of a DSA engine whose role is to perform real-time DSA of the power system, a wind power and load demand (W&LF) forecasting engine for offline and online predicting wind power generation and electricity load demand, a database generation (DBG) engine for generating instances to train the DSA engine, and a model updating (MU) engine for online updating the DSA engine. Case studies are conducted on two benchmark systems where high DSA efficiency and accuracy are obtained. This framework can be an ideal candidate for advanced security monitoring in the future SmartGrid control centres.
URI: http://hdl.handle.net/10397/27564
ISSN: 1551-3203
EISSN: 1941-0050
DOI: 10.1109/TII.2012.2206396
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

29
Last Week
0
Last month
0
Citations as of Sep 24, 2017

WEB OF SCIENCETM
Citations

25
Last Week
0
Last month
2
Citations as of Sep 22, 2017

Page view(s)

42
Last Week
0
Last month
Checked on Sep 24, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.