Compositive Load Model Based on Artificial Neural Network
Junying Song · Power System Technology · 2008
The authors point out the defects in the application of BP neural network in dynamic compositive load modeling; then propose a dynamic Elman neural network based load model that is suitable to describe dynamic characteristics of compositive load and possesses internal feedback function, and conduct the modeling for acquired samples of compositive load of a certain 220 kV substation by using improved genetic algorithm as optimization algorithm. A lot of modeling practices show that the proposed dynamic Elman neural network based compositive load model possesses such advantages as simple structure, less parameters, convenient to apply and strong ability to describe dynamic characteristics of compositive load etc. The Elman neural network is not only practicable for the modeling of dynamic load, but also a kind of neural network structure suitable to other dynamic nonlinear identifications in power system.