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本文针对电力负荷变化的非平稳性和周期性，采用灰色模型，可调灰色模型分析用电负荷的趋势项并与历史负荷比较得一系列残差，然后应用自回归模型，傅氏模型，人工神经网络模型进行修正以提高精度。用一系列组合模型分别用于不同场合和要求下的负荷预测，并在微机上开发软件，通过实例计算，效果良好，具有一定的应用价值
In this paper, aiming at the nonstationarity and periodicity of power load change, a gray model and an adjustable gray model are used to analyze the trend of electricity load and a series of residuals are compared with the historical load. Then, the autoregressive model, Fourier model, The neural network model is modified to improve the accuracy. A series of combination models are respectively used for load forecasting under different occasions and requirements. Software is developed on the microcomputer, and the calculation results are good and have certain application value