基于灰色神经网络组合模型的电力消费量预测——以河北省为例

在分析灰色预测模型GM(1,1)以及BP神经网络预测模型2种单一模型在电力消费量预测方面不足的基础上,提出灰色神经网络组合预测模型。以河北省电力消费量为基础,分别用3种模型进行预测,并加以比较分析。结果表明,灰色神经网络组合模型提高了关于河北省中长期电力消费量的预测精度,对河北省未来电力系统及能源需求规划具有一定参考价值。

Electric Power Consumption Forecasting Based on Gray Neural Network Model-- Taking Hebei Province as an Example

With the analysis of Gray model GM（1,1） and BP neural network model＇s deficiencies on the electric power consumption forecasting, this paper gives a combined gray neural network forecasting model. Based on the Electric Power Consumption in Hebei Province, three forecasting models are used to predict the Electric Power Consumption, and give a comparative analysis. The results show that the proposed combination model to further improve the prediction accuracy of long-term power consumption, and it has an application value.