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
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;
Conference_Titel :
Circuits and Systems, 1990., IEEE International Symposium on
Conference_Location :
New Orleans, LA
DOI :
10.1109/ISCAS.1990.112628