| 基于相空间重构ARIMA和SVR的母线净负荷预测 |
| |
| 引用本文： | 金山红,朱想,赫卫国,王波,梅飞,李玉杰,袁晓玲,刘皓明.基于相空间重构ARIMA和SVR的母线净负荷预测[J].电力需求侧管理,2018,20(2):20-24. |
| |
| 作者姓名： | 金山红 朱想 赫卫国 王波 梅飞 李玉杰 袁晓玲 刘皓明 |
| |
| 作者单位： | 国网浙江省电力公司嘉兴供电公司;中国电力科学研究院;国网浙江省电力公司宁波电力公司;河海大学能源与电气学院; |
| |
| 摘 要： | 为实现对含分布式电源母线净负荷的实时跟踪和预测,以分布式光伏并入电网的母线负荷情况为基础,根据净负荷本身固有的线性和非线性属性,提出了基于相空间重构自回归滑动平均(autoregressive moving arerage,ARIMA)和支持向量机(support vector machine,SVR)的母线净负荷预测方法。首先基于历史净负荷数据使用ARIMA建立拟合模型,对净负荷线性成分预测分析,之后用CC法对非线性成分进行相空间重构,利用SVR模型对非线性部分进行预测。数据建模的结果表明,提出的ARIMA-CC_SVR预测模型对含有分布式光伏成分的母线净负荷适用性较强。
|
| 关 键 词： | 净负荷预测 ARIMA CC法相空间重构 SVR |
Forecasting of bus.bar net load based on PSR.ARIMA and SVR |
| |
| IN Shan.hong,ZHU Xiang,HE Wei.guo,WANG Bo,MEI Fei,LI Yu.jie,YUAN Xiao.ling and LIU Hao.ming.Forecasting of bus.bar net load based on PSR.ARIMA and SVR[J].Power Demand Side Management,2018,20(2):20-24. |
| |
| Authors: | IN Shanhong ZHU Xiang HE Weiguo WANG Bo MEI Fei LI Yujie YUAN Xiaoling and LIU Haoming |
| |
| Affiliation: | Jiaxing Power Supply Company, State Grid Zhejiang Electric Power Company, Jiaxing 314000,China,China Electric Power Research Institute, Nanjing 210003, China,China Electric Power Research Institute, Nanjing 210003, China,Ningbo Power SupplyCompany, State Grid Zhejiang Electric Power Company, Ningbo 315000, China,College ofEnergy and Electrical Engineering, Hohai University, Nanjing 211100, China,College ofEnergy and Electrical Engineering, Hohai University, Nanjing 211100, China,College ofEnergy and Electrical Engineering, Hohai University, Nanjing 211100, China and College ofEnergy and Electrical Engineering, Hohai University, Nanjing 211100, China |
| |
| Abstract: | In order to realize the real.time tracking and fore.casting of net load with distributed power bus, in the light of the busload with distributed photovoltaic power grid, according to the linearand nonlinear properties of net load inherent, the autoregressivemoving average with the phase space reconstruction and support vec.tor machine bus.bar net load forecasting method is proposed.Firstly,based on the historical net load data, the ARIMA model is estab.lished to forecast the linear components of the net load.Then, thephase space of the nonlinear components is reconstructed by CCmethod.Finally, the nonlinear part is forecasted by the SVR model.The results of data modeling show that the proposed ARIMA .CC_SVR forecasting model is suitable for the net load of the bus.barwith distributed PV components. |
| |
| Keywords: | net load forecasting ARIMA CC method SVR |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《电力需求侧管理》浏览原始摘要信息 |
|
点击此处可从《电力需求侧管理》下载全文 |
|
