中国科学院沈阳自动化研究所机构知识库
Advanced  
SIA OpenIR  > 工业控制网络与系统研究室  > 期刊论文
题名: Research in residential electricity characteristics and short-term load forecasting
作者: Feng HX(冯海霞) ; Wang ZF(王忠锋) ; Ge WC(葛维春) ; Wang YN(王英男)
作者部门: 工业控制网络与系统研究室
关键词: Electricity ; Housing ; Linear regression ; Neural networks
刊名: Telkomnika
ISSN号: 1693-6930
出版日期: 2013
卷号: 11, 期号:12, 页码:7021-7026
收录类别: EI
产权排序: 1
摘要: In this paper we make research in Residential short-term load forecasting. Different application scenes have different affecting factors of short-term load, so we should specifically analysis of factors that affect the load of the residential electricity. We use SPSS (Statistic Package for Social Science) to figure out the relationship between the daily load and temperature, weather conditions and other factors, finding the main factors among the impacting factors, and analyzing residential electricity consumption habits and load characteristics. Then, the paper introduces the common prediction methods. Combining with the above analysis to choose short-term load forecasting methods for residential users, we create automatic linear regression model and artificial neural network model to predict the future electricity load, calculating the residual between the predicted values and the actual values and mean square deviation of the values, and evaluating the accuracy of the load forecasting. The results prove that automatic linear regression model is effective in residential short-term electricity load forecasting.
语种: 英语
内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/13998
Appears in Collections:工业控制网络与系统研究室_期刊论文

Files in This Item: Download All
File Name/ File Size Content Type Version Access License
Research in residential electricity characteristics and short-term load forecasting.pdf(266KB)----开放获取View Download

Recommended Citation:
冯海霞;王忠锋;葛维春;王英男.Research in residential electricity characteristics and short-term load forecasting,Telkomnika,2013,11(12):7021-7026
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[冯海霞]'s Articles
[王忠锋]'s Articles
[葛维春]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[冯海霞]‘s Articles
[王忠锋]‘s Articles
[葛维春]‘s Articles
Related Copyright Policies
Null
Social Bookmarking
Add to CiteULike Add to Connotea Add to Del.icio.us Add to Digg Add to Reddit
文件名: Research in residential electricity characteristics and short-term load forecasting.pdf
格式: Adobe PDF
此文件暂不支持浏览
所有评论 (0)
暂无评论
 
评注功能仅针对注册用户开放,请您登录
您对该条目有什么异议,请填写以下表单,管理员会尽快联系您。
内 容:
Email:  *
单位:
验证码:   刷新
您在IR的使用过程中有什么好的想法或者建议可以反馈给我们。
标 题:
 *
内 容:
Email:  *
验证码:   刷新

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.

 

 

Valid XHTML 1.0!
Copyright © 2007-2016  中国科学院沈阳自动化研究所 - Feedback
Powered by CSpace