DocumentCode :
2664174
Title :
A constrained optimization neural net technique for economic power dispatch
Author :
Maa, Chia-Yiu ; Chiu, Chinchuan ; Shanblatt, Michael A.
Author_Institution :
Dept. of Electr. Eng., Michigan State Univ., East Lansing, MI, USA
fYear :
1990
fDate :
1-3 May 1990
Firstpage :
2946
Abstract :
A linear programming neural network is extended to quadratic programming problems with both linear equality and inequality constraints. It is shown that the equilibrium of the quadratic programming network is asymptotically stable and is in the neighborhood of the minimizer of the objective function. The equilibrium can be made arbitrarily close to the minimizer of the objective function by choosing a parameter sufficiently large. An economic power dispatch problem is simulated to demonstrate the dynamic behavior of the proposed quadratic programming network
Keywords :
load dispatching; neural nets; quadratic programming; asymptotically stable; constrained optimization neural net; dynamic behavior; economic power dispatch; economic power dispatch problem; equilibrium; inequality constraints; linear equality; linear programming neural network; minimizer; objective function; quadratic programming problems; Artificial neural networks; Constraint optimization; Lagrangian functions; Linear programming; Neural networks; Optimization methods; Power generation economics; Power system economics; Quadratic programming; Telephony;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1990., IEEE International Symposium on
Conference_Location :
New Orleans, LA
Type :
conf
DOI :
10.1109/ISCAS.1990.112628
Filename :
112628
Link To Document :
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