灰色马尔可夫模型在城市电力消费预测中的应用

Application of Improved Grey Markov Model for Power Consumption Forecasting in City

传统的灰色预测模型只能反映月用电量的总体变化趋势,不能反映月用电量随季节的波动特征.为此,基于马尔可夫理论提出了灰色马尔可夫修正预测模型,研究了同时考虑两种趋势的城市月用电需求的预测问题.算例表明,与传统的预测方法相比,灰色马尔可夫修正的预测方法较好的提高了预测精度.

The traditional grey model reflects the general trend of the power consumption while failing to reflect the characteristics of seasonal fluctuation. The authors propose the grey correction model based on the Markov theory and study the problem of the demand of monthly electricity forecasting with double trends in the paper. The example shows that the combined optimum grey prediction method improved the accuracy of prediction, compared with the traditional methods.