基于高阶矩模型的电力负荷预测研究

The research on power load forecasting based on higher-order moment model

电力负荷预测对于电力企业合理制定生产计划,高效进行电网调度和控制具有重要意义.针对电力负荷序列展现出的时变特征,提出一种基于高阶矩模型的电力负荷预测方法.该方法使用广义自回归条件异方差偏度峰度模型提取电力负荷序列中的时变特征,通过结合参数估计和偏度峰度检验构建预测模型.实验表明,相比传统的4种基准方法,本文所提方法具有更好的预测性能.

Pow load forecasting is of great significance for power enterprises to make reasonable production plans and efficiently dispatch and control power grids.Aiming at the time-varying characteristics of power load series,a new novel approach for power load forecasting based on high-order moment model is proposed.This approach uses the Generalized Autoregressive Conditional Heteroscedasticity Skewness and Kuosis Model(GARCHSK)to extract the time-varying characteristics of power load series,and constructs the prediction model by combining parameter estimation and skewness kurtosis test.Experiments show that the proposed method has better prediction performance than the traditional four benchmark methods.