| 基于regARIMA模型的月度负荷预测效果研究 |
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| 引用本文： | 苏振宇,龙勇,赵丽艳. 基于regARIMA模型的月度负荷预测效果研究[J]. 中国电力, 2018, 51(5): 166-171. DOI: 10.11930/j.issn.1004-9649.201704041 |
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| 作者姓名： | 苏振宇 龙勇 赵丽艳 |
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| 作者单位： | 1. 重庆大学 经济与工商管理学院, 重庆 400030;2. 甘肃省电力公司培训中心, 甘肃 兰州 730070;3. 甘肃省电力科学研究院, 甘肃 兰州 730070 |
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| 基金项目： | 国家社会科学基金重点项目（14AZD130）。 |
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| 摘 要： | 为探究离群值对月度负荷预测效果的影响，建立计及离群值影响的季节性ARIMA月度负荷预测模型（regARIMA），选择1999-2017年北京、甘肃等5省（市）的实际月度负荷数据，对预测效果进行比较研究。结果表明，与普通ARIMA模型相比，考虑了离群值影响的regARIMA模型的3年样本内平均预测误差得到明显改善；应用regARIMA模型进行提前12期的样本外预测，预测精度获得不同程度的提升。
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| 关 键 词： | 月度负荷 负荷预测 离群值 regARIMA模型 |
| 收稿时间： | 2017-04-11 |
| 修稿时间： | 2018-02-10 |
Study on the Monthly Power Load Forecasting Performance Based on regARIMA Model |
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| SU Zhenyu,LONG Yong,ZHAO Liyan. Study on the Monthly Power Load Forecasting Performance Based on regARIMA Model[J]. Electric Power, 2018, 51(5): 166-171. DOI: 10.11930/j.issn.1004-9649.201704041 |
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| Authors: | SU Zhenyu LONG Yong ZHAO Liyan |
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| Affiliation: | 1. School of Economics and Business Administration, Chongqing University, Chongqing 400030, China;2. Gansu Electric Power Training Center, Lanzhou 730070, China;3. Gansu Electric Power Research Institute, Lanzhou 730070, China |
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| Abstract: | In order to explore the impact of outliers on the monthly power load forecasting performance, a seasonal ARIMA model considering the impact of outliers (regARIMA) is established. The actual monthly power load data series of 5 provinces recorded from January 1999 to December 2017 are used to verify the accuracy of power load forecasting. The empirical results show that the forecasting error of the regARIMA model considering the outliers impact is significantly reduced within samples for last 3 years. The forecasting accuracy of the regARIMA out of samples for 12 steps ahead is also improved to some extent. |
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| Keywords: | monthly power load power load forecasting outliers regARIMA model |
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