Abstract:In order to improve the prediction accuracy of short-term load, this paper proposes a short-term load prediction model based on support vector machine and ant colony optimization algorithm (ACO-SVM). Firstly, the data of short-term load are reconstructed by chaotic theory, and then the parameters of SVM were considered the position vector of ants, the optimal parameters are got by ACO, lastly, the optimal prediction model of short-term load is built and the performance of model is tested. The results show that ACO-SVM can describe the change rule of short-term load accurately and improves prediction accuracy.