Low-voltage distribution system planning under load demand uncertainty: Growth rate with connection of new loads

E. Gladkikh, M. Alvarez‐Herault, B. Raison, V. Vai, L. Bun
{"title":"Low-voltage distribution system planning under load demand uncertainty: Growth rate with connection of new loads","authors":"E. Gladkikh, M. Alvarez‐Herault, B. Raison, V. Vai, L. Bun","doi":"10.1109/IEECON.2017.8075739","DOIUrl":null,"url":null,"abstract":"This paper presents a novel algorithm to optimize a topology for tackling the challenge of increasing uncertainty on load demand (growth rate with connection of new loads) in low-voltage (LV) distribution. This paper aims at finding which load connection phase induces the lowest costs (investment and power losses) and phase balancing while satisfying the techno-economic aspects over planning study. A mixed integer quadratically constrained programming (MIQCP) and shortest path-bin packing with arborescence flow are developed to perform this work. To illustrate this method, the example of LV distribution (33 bus) is chosen to be a case study of an initial year. Monte-Carlo (MC) simulation method is employed to evaluate the results. The simulation results obtained on test system support an effectiveness of method.","PeriodicalId":196081,"journal":{"name":"2017 International Electrical Engineering Congress (iEECON)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Electrical Engineering Congress (iEECON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEECON.2017.8075739","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13

Abstract

This paper presents a novel algorithm to optimize a topology for tackling the challenge of increasing uncertainty on load demand (growth rate with connection of new loads) in low-voltage (LV) distribution. This paper aims at finding which load connection phase induces the lowest costs (investment and power losses) and phase balancing while satisfying the techno-economic aspects over planning study. A mixed integer quadratically constrained programming (MIQCP) and shortest path-bin packing with arborescence flow are developed to perform this work. To illustrate this method, the example of LV distribution (33 bus) is chosen to be a case study of an initial year. Monte-Carlo (MC) simulation method is employed to evaluate the results. The simulation results obtained on test system support an effectiveness of method.
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
负荷需求不确定性下的低压配电系统规划:随新负荷接入的增长率
本文提出了一种优化拓扑的新算法,以解决低压配电系统中负荷需求(随新负荷接入的增长率)不确定性增加的挑战。本文的目的是在满足技术经济方面的规划研究的同时,找出哪一个负荷连接阶段的成本(投资和功率损耗)和相位平衡最低。为此,提出了一种混合整数二次约束规划(MIQCP)和树形流下的最短路径装箱方法。为了说明这种方法,选择LV分布(33总线)作为第一年的案例研究。采用蒙特卡罗(MC)模拟方法对结果进行了评价。在测试系统上的仿真结果验证了该方法的有效性。
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
自引率
0.00%
发文量
0
期刊最新文献
Adaptive power flow control for reducing peak demand and maximizing renewable energy usage Fuzzy based random pulse width modulation technique for performance improvement of induction motor Condition evaluation of power transformers using dissolved gas analysis and dielectric breakdown voltage test The hybrid photovoltaic energy system for electric vehicle battery charger Analysis and modeling of wind turbine generators considering frequency controls
×
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