月刊
ISSN 1000-7229
CN 11-2583/TM
电力建设 ›› 2022, Vol. 43 ›› Issue (9): 117-124.doi: 10.12204/j.issn.1000-7229.2022.09.012
• 新型电力系统下配电网规划与运行优化关键技术研究及应用·栏目主持 王守相教授、赵倩宇博士· • 上一篇 下一篇
收稿日期:
2021-11-25
出版日期:
2022-09-01
发布日期:
2022-08-31
通讯作者:
朱威
E-mail:zhuwei_ok@126.com
作者简介:
孙玉芹(1971),女,博士,教授,主要研究方向为组合数学与图论、智能电网优化;基金资助:
SUN Yuqin, WANG Yawen, ZHU Wei(), LI Yan
Received:
2021-11-25
Online:
2022-09-01
Published:
2022-08-31
Contact:
ZHU Wei
E-mail:zhuwei_ok@126.com
Supported by:
摘要:
由于气温突变点的影响,负荷序列存在门限效应,导致传统线性时间序列模型的负荷预测效果较差。将气温突变点作为门限,建立了以气温为协变量的门限自回归移动平均(threshold autoregressive moving average with exogenous variable,TARMAX)模型,提高了预测精度。首先,应用马尔科夫链蒙特卡洛(Markov chain Monte Carlo,MCMC)方法对气温突变点进行搜寻得到模型参数。然后,采用随机搜索变量的方法快速选择出最优模型,有效降低选择时间序列模型的计算量。最后,对不同季节下的居民日用电负荷进行预测。实例表明,与线性时间序列模型、长短期记忆网络(long short-term memory network,LSTM)和多层感知机(multilayer perceptron, MLP)相比,TARMAX模型提高了电力负荷的预测精度。
中图分类号:
孙玉芹, 王亚文, 朱威, 李彦. 基于考虑气温影响的门限自回归移动平均模型居民日用电负荷预测[J]. 电力建设, 2022, 43(9): 117-124.
SUN Yuqin, WANG Yawen, ZHU Wei, LI Yan. Residential Daily Power Load Forecasting Based on Threshold ARMA Model Considering the Influence of Temperature[J]. ELECTRIC POWER CONSTRUCTION, 2022, 43(9): 117-124.
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