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基于改良灰色理论的电网短期负荷预测算法
Short Term Load Forecasting Algorithm Based on Improved Grey Theory
【摘要】 在分析传统灰色负荷预测理论与GM(1,n)模型的基础上,再次对GM(1,n)模型进行改进,以解决由于传统的灰色理论对原始数据要求的严格造成预测结果误差较大的问题。实验表明,用此方法建立的负荷预测模型,在预测精度上有较大的提高,为今后灰色理论模型的改进提供了一定的依据。
【Abstract】 Based on the analysis of the traditional grey load forecasting theory and GM( 1,n) model,the GM( 1,n) model is improved again to solve the problem of large error of forecasting results due to the strict requirements of the traditional grey theory on the original data. The experiment shows that the load forecasting model established by this method has a great improvement in the forecasting accuracy,which will be helpful for the future grey theory.
【基金】 国家自然科学基金资助项目(61961025);江西省科技厅项目(20151BBE50103)
- 【文献出处】 计算机与现代化 ,Computer and Modernization , 编辑部邮箱 ,2021年03期
- 【分类号】TM715
- 【被引频次】5
- 【下载频次】145