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 :
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