多维优化器在电力系统输电网扩容规划中的应用

A. Shaheen, R. El-Sehiemy
{"title":"多维优化器在电力系统输电网扩容规划中的应用","authors":"A. Shaheen, R. El-Sehiemy","doi":"10.1109/ITCE.2019.8646329","DOIUrl":null,"url":null,"abstract":"Transmission Network Expansion Planning (TNEP) is an important issue in electrical power systems. It is a mixed integer, non-linear, non-convex optimization problem which aims to optimal selection of the routs, types, and number of the added circuits to face the expected future predicted load forecasting at minimum costs. This paper proposes the application of Multi-Verse Optimizer (MVO) for solving the TNEP with security constraints. MVO has various merits of being simple structure, having adaptive control parameter, and operating with high ability to escape the local optima stagnation. The MVO has been developed and applied to solve the TNEP problem for two realistic transmission Egyptian networks of West Delta System (WDS) and 500 kV of Extra High Voltage System (EHVS). The predicted load forecasting up to 2030 is considered based on the adaptive neuro-fuzzy inference system (ANFIS). The simulation results for the two systems show the capability of the proposed MVO to solve efficiently the TNEP problem. The MVO superiority is proven to produce economic planning and secure transmission routes.","PeriodicalId":391488,"journal":{"name":"2019 International Conference on Innovative Trends in Computer Engineering (ITCE)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":"{\"title\":\"Application of multi-verse optimizer for transmission network expansion planning in power systems\",\"authors\":\"A. Shaheen, R. El-Sehiemy\",\"doi\":\"10.1109/ITCE.2019.8646329\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Transmission Network Expansion Planning (TNEP) is an important issue in electrical power systems. It is a mixed integer, non-linear, non-convex optimization problem which aims to optimal selection of the routs, types, and number of the added circuits to face the expected future predicted load forecasting at minimum costs. This paper proposes the application of Multi-Verse Optimizer (MVO) for solving the TNEP with security constraints. MVO has various merits of being simple structure, having adaptive control parameter, and operating with high ability to escape the local optima stagnation. The MVO has been developed and applied to solve the TNEP problem for two realistic transmission Egyptian networks of West Delta System (WDS) and 500 kV of Extra High Voltage System (EHVS). The predicted load forecasting up to 2030 is considered based on the adaptive neuro-fuzzy inference system (ANFIS). The simulation results for the two systems show the capability of the proposed MVO to solve efficiently the TNEP problem. The MVO superiority is proven to produce economic planning and secure transmission routes.\",\"PeriodicalId\":391488,\"journal\":{\"name\":\"2019 International Conference on Innovative Trends in Computer Engineering (ITCE)\",\"volume\":\"86 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Innovative Trends in Computer Engineering (ITCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITCE.2019.8646329\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Innovative Trends in Computer Engineering (ITCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITCE.2019.8646329","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 26

摘要

输电网扩容规划是电力系统中的一个重要问题。它是一个混合整数、非线性、非凸优化问题,旨在以最小的成本优化选择增加电路的路由、类型和数量,以面对预期的未来预测负荷预测。本文提出了应用多重宇宙优化器(Multi-Verse Optimizer, MVO)来解决具有安全约束的TNEP问题。MVO具有结构简单、控制参数自适应、运行时摆脱局部最优停滞能力强等优点。开发并应用于西三角洲系统(WDS)和500kv特高压系统(EHVS)两个埃及实际输电网络的TNEP问题。研究了基于自适应神经模糊推理系统(ANFIS)的2030年前电力负荷预测问题。两个系统的仿真结果表明,所提出的MVO能够有效地解决TNEP问题。MVO的优越性被证明可以产生经济的规划和安全的传输路线。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Application of multi-verse optimizer for transmission network expansion planning in power systems
Transmission Network Expansion Planning (TNEP) is an important issue in electrical power systems. It is a mixed integer, non-linear, non-convex optimization problem which aims to optimal selection of the routs, types, and number of the added circuits to face the expected future predicted load forecasting at minimum costs. This paper proposes the application of Multi-Verse Optimizer (MVO) for solving the TNEP with security constraints. MVO has various merits of being simple structure, having adaptive control parameter, and operating with high ability to escape the local optima stagnation. The MVO has been developed and applied to solve the TNEP problem for two realistic transmission Egyptian networks of West Delta System (WDS) and 500 kV of Extra High Voltage System (EHVS). The predicted load forecasting up to 2030 is considered based on the adaptive neuro-fuzzy inference system (ANFIS). The simulation results for the two systems show the capability of the proposed MVO to solve efficiently the TNEP problem. The MVO superiority is proven to produce economic planning and secure transmission routes.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
System Design and Implementation of Wall Climbing Robot for Wind Turbine Blade Inspection Application of Fuzzy Logic on Astronomical Images Focus Measure Comparative Evaluation of PWM Techniques Used at Mega 328/p with PI Control for Inverter-Fed Induction Motor Simulating The Thermoelectric Behaviour of CNT Based Harvester Characterization of the sources of degradation in remote sensing satellite images
×
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