Solving of Interval DC Power Flow using Interval Hull Algorithm with Preconditioning

Q1 Engineering 电力系统自动化 Pub Date : 2014-01-01 DOI:10.7500/AEPS201301001
Tao Ding, Qinglai Guo, R. Bo, W. Gu, Hongbin Sun, Boming Zhang
{"title":"Solving of Interval DC Power Flow using Interval Hull Algorithm with Preconditioning","authors":"Tao Ding, Qinglai Guo, R. Bo, W. Gu, Hongbin Sun, Boming Zhang","doi":"10.7500/AEPS201301001","DOIUrl":null,"url":null,"abstract":"With intermittent sources integrated into the power grid,power flows of the power grid are getting stochastic. Considering the uncertainty problem of DC power flow in the high voltage transmission system,this paper recommends an interval Hull algorithm with preconditioning to solve the interval DC power flow.Firstly,the diagonal dominant interval coefficient matrix is formed by preconditioning,then the H-matrix is obtained using the interval Hull algorithm.Different approximation methods are employed for the comparison matrix of H-matrix to improve precision.And the upper and lower bound of the distribution of interval DC power flow is obtained with the iterative method.The interval Hull algorithm and Monte Carlo algorithm are compared in the 9-bus test system,the result of which shows that the uncertainty in grid parameters is the main cause of errors.Furthermore,the Hull algorithm with preconditioning,the interval Hull method,the Krawczyk operator iteration method and the Gauss elimination method are compared in terms of accuracy and computing time on an IEEE 57-bus and an IEEE 118-bus test system,respectively.It is shown that the Hull method with preconditioning has the best accuracy,and the time complexity is far lower than that of the Monte Carlo algorithm.","PeriodicalId":52447,"journal":{"name":"电力系统自动化","volume":"38 1","pages":"130-136"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"电力系统自动化","FirstCategoryId":"1087","ListUrlMain":"https://doi.org/10.7500/AEPS201301001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 5

Abstract

With intermittent sources integrated into the power grid,power flows of the power grid are getting stochastic. Considering the uncertainty problem of DC power flow in the high voltage transmission system,this paper recommends an interval Hull algorithm with preconditioning to solve the interval DC power flow.Firstly,the diagonal dominant interval coefficient matrix is formed by preconditioning,then the H-matrix is obtained using the interval Hull algorithm.Different approximation methods are employed for the comparison matrix of H-matrix to improve precision.And the upper and lower bound of the distribution of interval DC power flow is obtained with the iterative method.The interval Hull algorithm and Monte Carlo algorithm are compared in the 9-bus test system,the result of which shows that the uncertainty in grid parameters is the main cause of errors.Furthermore,the Hull algorithm with preconditioning,the interval Hull method,the Krawczyk operator iteration method and the Gauss elimination method are compared in terms of accuracy and computing time on an IEEE 57-bus and an IEEE 118-bus test system,respectively.It is shown that the Hull method with preconditioning has the best accuracy,and the time complexity is far lower than that of the Monte Carlo algorithm.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
带预处理的区间船体算法求解区间直流潮流
随着间歇性电源并网,电网的潮流变得越来越随机。针对高压输电系统中直流潮流的不确定性问题,提出了一种带预处理的区间赫尔算法来求解区间直流潮流。首先通过预处理形成对角优势区间系数矩阵,然后利用区间Hull算法得到h矩阵。对h矩阵的比较矩阵采用了不同的近似方法,以提高精度。用迭代法求出区间直流潮流分布的上界和下界。在9总线测试系统中对区间赫尔算法和蒙特卡罗算法进行了比较,结果表明网格参数的不确定性是产生误差的主要原因。在IEEE 57总线和IEEE 118总线测试系统上,分别比较了带预处理的Hull算法、区间Hull法、Krawczyk算子迭代法和高斯消去法的精度和计算时间。结果表明,带预处理的赫尔法具有最好的精度,且时间复杂度远低于蒙特卡罗算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
电力系统自动化
电力系统自动化 Energy-Energy Engineering and Power Technology
CiteScore
8.20
自引率
0.00%
发文量
15032
期刊介绍: Founded in 1977, Power System Automation is a well-known journal in the discipline of electrical engineering in China. At present, it has been issued to all provinces, cities, autonomous regions, Hong Kong, Macao and Taiwan, and abroad to dozens of countries in North America, Europe and Asia-Pacific region, with a large number of readers at home and abroad. Power System Automation takes “based on China, facing the world, seeking truth and innovation, promoting scientific and technological progress in the field of electric power and energy” as the purpose of the journal, mainly for the professional and technical personnel, teachers and students engaged in scientific research, design, operation, testing, manufacturing, management and marketing in the electric power industry and higher education institutions as well as electric power users, and focuses on hotspots of the industry's development and the It focuses on the hot and difficult issues of the industry. It focuses on the hot and difficult issues of the industry, both academic and forward-looking, practical and oriented, and at the same time emphasizes and encourages technical exchanges of experiences, improvements and innovations from the front line of scientific research and production.
期刊最新文献
Active Frequency Drift Islanding Detection Technology with Feedback of Load Impedance Angle Coordinated heat and power dispatch of microgrid considering two-dimensional controllability of heat loads Fault tolerance ability analysis and evaluation of three-phase voltage source converters Calculation method of nodal price in distribution network considering power supply reliability A Coordinated Charging Strategy for Electric Vehicle Three-phase Load Balance
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1