| 基于ARIMA和LS-SVM组合模型的短期负荷预测 |
| |
| 引用本文： | 刘国徽,刘小满,余雪芳,王勇. 基于ARIMA和LS-SVM组合模型的短期负荷预测[J]. 广东电力, 2010, 23(11): 14-17 |
| |
| 作者姓名： | 刘国徽 刘小满 余雪芳 王勇 |
| |
| 作者单位： | 东北电力大学,吉林,吉林,132012;东北电网有限公司长春超高压局,吉林,长春,130041 |
| |
| 摘 要： | 经实例预测分析发现,利用累积式自回归动平均法(autoregressive integrated moving average,ARIMA)进行电力短期负荷预测时所得误差序列有较明显的周期规律性,针对此现象及其原因,为提高预测精度,提出采用最小二乘支持向量机(least squares support vector machine,LS-SVM)对ARIMA预测误差进行修正的ARIMA-LS-SVM组合模型;利用该改进模型对哈尔滨电网负荷进行实例预测,结果表明:该方法能够提高短期负荷的预测精度,并且具有较强的推广性和应用能力。
|
| 关 键 词： | 短期负荷预测 ARIMA模型 LS-SVM模型 偏差修正 |
Short-term Load Forecasting Based on ARIMA-LS-SVM Model |
| |
| LIU Guo-hui,LIU Xiao-man,YU Xue-fang,WANG Yong. Short-term Load Forecasting Based on ARIMA-LS-SVM Model[J]. Guangdong Electric Power, 2010, 23(11): 14-17 |
| |
| Authors: | LIU Guo-hui LIU Xiao-man YU Xue-fang WANG Yong |
| |
| Affiliation: | LIU Guo-hui1,LIU Xiao-man1,YU Xue-fang1,WANG Yong2(1.Northeast Dianli Univ.,Jilin,Jilin 132012,China,2.Changchun Extrahigh Voltage Bureau of Northeast China Grid Co.,Ltd.,Changchun 130041,China) |
| |
| Abstract: | It is found through forecasting case study that the error sequence has obvious cycle regularity while using autoregressive integrated moving average(ARIMA) in short-term power load forecasting.For this phenomenon and its reason,an ARIMA-LS-SVM model,which uses least squares support vector machine(LS-SVM) to correct the error of ARIMA forecasting,is proposed to improve forecasting accuracy.Using this improved model to the load forecasting of Harbin power grid,the results indicate that the model can improve t... |
| |
| Keywords: | short-term load forecasting ARIMA model LS-SVM model error correction |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
