基于改进的灰色模型的煤矿电力短期负荷预测

Short-Term Load Forecasting of Coal Mine Power Based on Improved Grey Mode

中文关键词:  人工蜂群算法  灰色模型  灰色关联度  煤矿电力负荷预测

英文关键词:artificial bee colony  grey model  grey correlation degree  coal mine power load forecasting

中文摘要:

      为了提高煤矿电力负荷预测的精度，解决传统灰色模型的缺陷，建立了改进的灰色模型。将背景值进行优化生成权重系数，通过人工蜂群算法找出合适的背景值生成权重系数，以误差最小为目标，得到了负荷预测值。通过Matlab R2012a仿真，与传统的灰色模型相比，该模型的预测精度更高，证明该方法是有效的。

英文摘要:

      In order to overcome the shortcomings of traditional grey model and improve the precision of power load forecasting,an improved grey model is established.The background value was optimized to generate weight coefficients.The artificial bee colony algorithm was used to find the appropriate background value to generate the weight coefficients,and the minimum load was taken as the target.The experiment is done by Matlab,the accuracy of load forecasting is higher than that of the traditional GM (1,1),which proves that the new method is effective.