A SIMULATION STUDY ON LOAD MODELING OF A THERMAL POWER UNIT BASED ON WAVELET NEURAL NETWORKS

Thermal power unit is a complex object with multi-variables. It is difficult to build its nonlinear mathematic model in an usual way. This paper presents a simulation study on load modeling of a thermal power unit by a kind of multi-input-multi-output continual WNN model. The linear function and wavelet basis function satisfying the frame condition are employed as an activation function in output and hidden layer respectively, and BP arithmetic is used to train it, and self-adaptive learning rate and momentum coefficient are also used to accelerate the learning speed. The simulation results show that difference between the output value of WNN and the one of real model is in permissible range. WNN can approach the model of a thermal power unit very well.