[1]王玉荣,万秋兰,陈昊.基于两重门限GARCH模型的短期负荷预测[J].东南大学学报(自然科学版),2011,41(6):1182-1187.[doi:10.3969/j.issn.1001-0505.2011.06.011]
 Wang Yurong,Wan Qiulan,Chen Hao.Short term load forecasting based on double-threshold GARCH models[J].Journal of Southeast University (Natural Science Edition),2011,41(6):1182-1187.[doi:10.3969/j.issn.1001-0505.2011.06.011]
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基于两重门限GARCH模型的短期负荷预测()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
41
期数:
2011年第6期
页码:
1182-1187
栏目:
电气工程
出版日期:
2011-11-20

文章信息/Info

Title:
Short term load forecasting based on double-threshold GARCH models
作者:
王玉荣1万秋兰1陈昊12 
(1东南大学电气工程学院, 南京 210096)
(2江苏省电力公司, 南京 210019)
Author(s):
Wang Yurong1Wan Qiulan1Chen Hao12
(1School of Electrical Engineering, Southeast University, Nanjing 210096, China)
(2Jiangsu Electric Power Company, Nanjing 210019, China)
关键词:
两重门限GARCH模型 厚尾效应 混合信息冲击曲面 短期负荷预测
Keywords:
double-threshold generalized auto-regressive conditional heteroskedasticity (DT-GARCH) model fat-tail effect hybrid news impact surface short term load forecasting
分类号:
TM714
DOI:
10.3969/j.issn.1001-0505.2011.06.011
摘要:
针对负荷时间序列的非线性和波动性特征,在研究负荷时间序列波动性门限特征的基础上,引入冲量门限的概念,提出了一种基于两重门限GARCH模型的短期负荷预测新方法.利用条件极大似然估计方法,估计了模型参数.同时,考虑到负荷时间序列波动的厚尾效应,将模型推广为服从非高斯分布假设下的情形,建立了2种基于厚尾假设的两重门限GARCH类负荷预测模型.利用所提出的混合信息冲击曲面,分析了不同性质的冲击和冲量对负荷时间序列波动性的影响.实际算例基于南京地区日用电量数据进行了短期负荷预测,验证了模型及方法的可行性和有效性.算例结果表明,服从广义误差分布的两重门限GARCH模型预测效果满意.
Abstract:
Considering the nonlinearity and volatility of load time series, threshold characteristics in load time series are analyzed. The concept of momentum threshold is employed and a novel double-threshold generalized auto-regressive conditional heteroskedasticity (DT-GARCH) model is proposed for short term load forecasting. By using the conditional maximum likelihood estimation (CMLE), the parameters are estimated. In addition, with fat-tail effect in volatility, the proposed models with non-Gaussian distributions are highlighted and estimated. Furthermore, the hybrid news impact surface is proposed to help analyze the impact of different shocks and momentums to the load time series. In case study, short term load forecasting is carried out based on the historical daily power consumption data of Nanjing, which validates the feasibility and effectiveness of the proposed model. Numerical results indicate that the DT-GARCH model with generalized error distribution provides satisfying forecasting results.

参考文献/References:

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备注/Memo

备注/Memo:
作者简介: 王玉荣(1981—),女,博士生; 万秋兰(联系人),女,博士,教授,博士生导师,qlwan@seu.edu.cn.
引文格式: 王玉荣,万秋兰,陈昊.基于两重门限GARCH模型的短期负荷预测[J].东南大学学报:自然科学版,2011,41(6):1182-1187. [doi:10.3969/j.issn.1001-0505.2011.06.011]
更新日期/Last Update: 2011-11-20