DocumentCode
285172
Title
Neural networks for generation scheduling in power systems
Author
Liu, Z.J. ; Villaseca, F.E. ; Renovich, F., Jr.
Author_Institution
Dept. of Electr. Eng., Cleveland State Univ., OH, USA
Volume
2
fYear
1992
fDate
7-11 Jun 1992
Firstpage
233
Abstract
A neural network for generation scheduling in power systems is presented. The network consists of two levels which correspond to different types of variables in the generation scheduling problem. The first level is a neural net which solves economic dispatch, a sub-problem in the generation scheduling problem. Its outputs indicate the power generation of generating units. The second level is a Boltzmann machine, a stochastic neural net which determines the off/on status of units. Simulation on a 20 generating-unit system shows that fast and optimal solutions can be obtained using the proposed neural network
Keywords
Boltzmann machines; power system computer control; Boltzmann machine; economic dispatch; generation scheduling; neural networks; power systems; simulation; stochastic neural net; Computational modeling; Costs; Intelligent networks; Neural networks; Power generation; Power generation economics; Power systems; Processor scheduling; Production systems; Spinning;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location
Baltimore, MD
Print_ISBN
0-7803-0559-0
Type
conf
DOI
10.1109/IJCNN.1992.227002
Filename
227002
Link To Document