摘要
针对短期电力负荷预测的特点,提出了更适合负荷预测模型,对传统灰色预测模型的局限性进行了改进。采用三点平滑处理削弱了个别不理想数据对整个数据序列的影响,对GM(1,1)模型进行了残值修正,建立了针对后验差检验不合格情况下的新的GM(1,1)模型。通过实证分析与相对误差的比较,该模型具有良好的适应性,可大大提高预测的精度。
According to the characteristics of the short-term power load forecasting, the paper puts forward more suitable forecasting model for short term power load forecasting, and it improves the limitations of traditional grey forecasting model. The three points smooth processing weakens the influences of unsatisfactory data to the whole data sequence, and the paper modifies salvage value of GM （1, 1 ） and establish new GM （1, 1） model in the circumstance of unqualified posterior difference test. Through the empirical analysis and relative error comparison, this model has a good adaptability and it greatly improves the accuracy of prediction..
出处
《山东电力高等专科学校学报》
2013年第3期5-7,16,共4页
Journal of Shandong Electric Power College
