差异演化算法优化灰色模型的负荷预测

Optimization of Gray Load Prediction Model by Differential Evolution Algorithm

传统灰色预测模型GM(1,1)在预测增长较快的电力负荷时预测效果会变差,为克服这一缺陷,首先对原始数据进行开次方处理使数据增长变平稳,再将差异演化算法与GM(1,1)模型相结合,利用差异演化算法求解GM(1,1)模型中的参数。电力负荷预测实例结果表明该模型具有较高的预测精度和较广的应用范围。

When predicting the fast-growing electric load, the prediction result of gray prediction model GM （1,1） is bad. In order to overcome this shortcoming, it first needs to extract the original data so that the data growth becomes stable, then combine differential evolution algorithm with GM （1,1） model, and solve the parameters of GM （1,1） model by differential evolution algorithm. Instances of power load prediction results show that the model has higher prediction accuracy and a wide range of applications.