DocumentCode
2294346
Title
Neural network optimal-power-flow
Author
Nguyen, T.T.
Author_Institution
Western Australia Univ., Nedlands, WA, Australia
Volume
1
fYear
1997
fDate
11-14 Nov 1997
Firstpage
266
Abstract
The paper develops a massively-parallel computing structure based on arrays of neural networks to solve the optimal power flow (OPF) problem. The context of its application is in EMS (energy management systems) relating to finding optimal operating states for an interconnected power network system where the total load demand which the system is required to supply is specified. A principal feature of the neural network OPF is that it offers ultra-highspeed computation. It provides parallel computation and, at the same time, takes full advantage of sparsity of the matrixes encountered in ORE
Keywords
power system analysis computing; EMS; computer simulation; energy management systems; interconnected power network; massively-parallel computing structure; neural network arrays; optimal operating states; optimal power flow; parallel computation; power systems; sparse matrix; total load demand; ultra-highspeed computation;
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:19971842
Filename
726881
Link To Document