灰色模型在短期电力负荷预测中的应用

电力负荷预测是电力控制及运行方面的最重要的一项任务，根据不同的预测对象，常用的方法有概率统计法、时间序列分析及灰色系统等等。文章讨论了灰色模型GM(1，1)及其改进模型在短期电力负荷预测中的应用。采用ARIMA(p,d,q)模型与GM(1，1)改进模型对特殊日电力负荷进行组合预测，提出了适合电网特殊日电力负荷预测的数据处理方法。提高了预测的精度。准确度到了95%以上，解决了每日24点正点采样情况下预测精度较低的问题。

The application of gray model in the electric power load forecasting

Electric power load forecasting is one of the important tasks in electric power control and operation. According to different forecasting objectives, the usual methods include probability statistics methods, time sequence analysis and grey system ,etc.In this paper ,the application of grey model GM(1,1) and its improved model in the electric power load forecasting is presented, GM(1,1) improving model and ARIMA(p,d,q)model are used to combinately forecast the special daily power load.The method which is suitable for the forecasting data is founded,thus the precision of forecasting has been improved,which is better than 95%,and the problem of low accurate forecast has been solved.