DocumentCode :
2152510
Title :
On-line security optimisation of large power systems using artificial intelligence techniques
Author :
Nicholson, B.A. ; Dunn, R.W.
Author_Institution :
Sch. of Electron. & Electr. Eng., Bath Univ., UK
Volume :
2
fYear :
1997
fDate :
11-14 Nov 1997
Firstpage :
579
Abstract :
This paper presents a method for the robust on-line optimisation of power system transient stability and economy. It is intended that such a tool will be able to continually adapt to on-line changes in demand and availability in a power system and provide advice to power system operators to allow substantial cost savings and reduce the need for additional power system reinforcement. A detailed description of the method, which utilises the power of three different artificial intelligence techniques, is presented. This is accompanied by the results of a series of tests which demonstrate both the overall suitability of the method and clearly show a substantial improvement over traditional optimisation techniques
Keywords :
power system security; artificial intelligence techniques; cost savings; genetic algorithms; neural network stability assessor; on-line security optimisation; power system economy; power system operators; power system transient stability; power systems; robust on-line optimisation;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Advances in Power System Control, Operation and Management, 1997. APSCOM-97. Fourth International Conference on (Conf. Publ. No. 450)
Print_ISBN :
0-85296-912-0
Type :
conf
DOI :
10.1049/cp:19971899
Filename :
724912
Link To Document :
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