Title :
An application of neural network to dynamic dispatch using multi processors
Author :
Fukuyama, Yoshikazu ; Ueki, Yoshiteru
Author_Institution :
Fuji Electr. Corp. Res. & Dev. Ltd., Tokyo, Japan
fDate :
11/1/1994 12:00:00 AM
Abstract :
This paper presents an application of neural networks to dynamic dispatch. The proposed method uses a neural network with appropriate noises and can give efficient initial neuron conditions which are specific to the problem. Therefore, convergence to a local minimum can be suppressed. The method is implemented on a transputer, that is one of the efficient parallel processors, and the appropriate number of processors is examined. It can develop optimal and feasible generator output trajectories quickly by applying forecasts of system load patterns to practical thermal generating unit systems
Keywords :
load dispatching; load forecasting; neural nets; parallel processing; power system analysis computing; thermal power stations; transputers; Hopfield neural net; convergence suppression; dynamic dispatch; generator output trajectories; initial neuron conditions; multi processors; neural network application; parallel processors; power system automation; system load patterns forecasting; thermal generating unit; transputer; Demand forecasting; Load forecasting; Load management; Neural networks; Power generation; Power system dynamics; Power systems; Supply and demand; Thermal loading; Thermal stresses;
Journal_Title :
Power Systems, IEEE Transactions on