基于改进型Elman神经网络龋短期电力负荷预测

精确的短期电力负荷预测对电力系统的生产调度和安全稳定运行起到十分重要的作用。为提高短期电力负荷预测模型的精度。提出了一种基于Elman神经网络的改进模型。通过在输出层和隐含层之间扩展一个新的承接层。增强了Elman神经网络的动态信息处理能力。仿真结果表明，改进型Elman神经网络预测模型的预测精度要高于反向传播、支持向量机和常规Elman，同时也说明了建立改进型Elman模型用于短期电力负荷预测是可行的。

Short-term Load Forecast Based on Improved Elman Neural Network

Precise short-terln load forecasting plays an important role in production dispatching and secure and stable operation. To improve the precision of the short-term load forecasting model, this paper proposes a short-term load forecasting model based on the improved Elman neural network. A new layer is added between the output layer and the hidden layer, which enhances information processing capabilities of the Elman neural network. Simulation results show that proposed model has a higher forecasting accuracy than BP, SVM and regular Elman, and it is effective and feasible.