Abstract:

A support vector regression optimized by genetic algorithm model was developed for grid host load prediction. Genetic algorithm and cross validation technology were applied to solve parameter optimization of support vector regression. Simulation experiments were performed on benchmark data set. Experimental results indicate that the proposed model exhibits better performance than support vector regression model with parameters selected by trialanderror method and the backpropagation neural network.

Key words: grid host load prediction, support vector regression, genetic algorithm