基于新陈代谢灰色马尔可夫模型的工业园区用电量预测

Electricity demand forecasting of industrial park based on metabolism grey Markov model

单一的灰色预测模型只能反映工业园区月用电量的总体变化情况,无法反映用电量随生产计划和季节变化的波动特点。为此,将灰色预测、新陈代谢法与马尔可夫理论三者的设计思想相融合,优化灰色模型的维数,引入马尔可夫修正系数,建立新的改进模型。通过案例的分析研究,新陈代谢灰色马尔可夫模型能够较好的提高预测的精度。

A single gray prediction model can only reflect the overall changes of the monthly electrical load in the industrial park, but can＇t reflect the characteristics of the power load fluctuations with production planning and seasonal variation. To this end, three design ideas of the gray prediction, metabolic theory and Markov method are integrated. Dimension of gray model is optimized. Markov correction factor is introduced to create a new improved model. By analyzing and studying the case, the metabolic Markov model can improve the prediction accuracy.