多分布代的最佳分配和大小:逐步注入

Emad Ali Almabsout, Naser Elnaily, M. Majidi, Ahmad Ali Nazeri
{"title":"多分布代的最佳分配和大小:逐步注入","authors":"Emad Ali Almabsout, Naser Elnaily, M. Majidi, Ahmad Ali Nazeri","doi":"10.1109/ICEMIS56295.2022.9914272","DOIUrl":null,"url":null,"abstract":"The demand for energy is increased by increasing global population and rapid developments in the current industry and modern lifestyle. It is a necessity to promote and modernize the control systems of the electrical network and move forward to the green and smart energy systems. The integration of the distributed generations (DGs) with the optimum capacity and position is one of the viable keys for reducing the active and reactive power losses, providing standard system power quality, and also injecting more renewable energy sources into the system in order to extend decarbonized and green systems. The Optimal DG (ODG) allocation and sizing have always been challenging for both suppliers and consumers/prosumers. The fundamental objectives of ODG are to enhance system overall efficiency with reduced power losses, maximize system security, voltage stability, and reliability. This paper proposes the implementation of the Grey Wolf (GWO) as state of the art for the nonlinear meta-heuristic optimization algorithm to solve ODG in the radial distribution system. The optimization aims are to reduce the percentage of daily power losses and voltage fluctuation of the radial systems. The GWO is applied to implement multiple DGs, by considering step-by-step injection strategy, to the IEEE 69 bus distribution test system. Two different scenarios are taking into account: the common DG with the fixed capacity to inject both active and reactive power to the system and time-series output for a photovoltaic generation which considered as a DC-battery.","PeriodicalId":191284,"journal":{"name":"2022 International Conference on Engineering & MIS (ICEMIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimum Allocation and Sizing of Multi-Distributed Generations: Step-by-Step Injection\",\"authors\":\"Emad Ali Almabsout, Naser Elnaily, M. Majidi, Ahmad Ali Nazeri\",\"doi\":\"10.1109/ICEMIS56295.2022.9914272\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The demand for energy is increased by increasing global population and rapid developments in the current industry and modern lifestyle. It is a necessity to promote and modernize the control systems of the electrical network and move forward to the green and smart energy systems. The integration of the distributed generations (DGs) with the optimum capacity and position is one of the viable keys for reducing the active and reactive power losses, providing standard system power quality, and also injecting more renewable energy sources into the system in order to extend decarbonized and green systems. The Optimal DG (ODG) allocation and sizing have always been challenging for both suppliers and consumers/prosumers. The fundamental objectives of ODG are to enhance system overall efficiency with reduced power losses, maximize system security, voltage stability, and reliability. This paper proposes the implementation of the Grey Wolf (GWO) as state of the art for the nonlinear meta-heuristic optimization algorithm to solve ODG in the radial distribution system. The optimization aims are to reduce the percentage of daily power losses and voltage fluctuation of the radial systems. The GWO is applied to implement multiple DGs, by considering step-by-step injection strategy, to the IEEE 69 bus distribution test system. Two different scenarios are taking into account: the common DG with the fixed capacity to inject both active and reactive power to the system and time-series output for a photovoltaic generation which considered as a DC-battery.\",\"PeriodicalId\":191284,\"journal\":{\"name\":\"2022 International Conference on Engineering & MIS (ICEMIS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Engineering & MIS (ICEMIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEMIS56295.2022.9914272\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Engineering & MIS (ICEMIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEMIS56295.2022.9914272","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

随着全球人口的增加,工业和现代生活方式的快速发展,对能源的需求也在增加。推进电网控制系统现代化,向绿色、智能能源系统迈进是必然的。将具有最佳容量和位置的分布式发电机组(dg)进行集成,是降低有功和无功损耗、提供标准的系统电能质量以及向系统注入更多可再生能源以扩展脱碳和绿色系统的可行关键之一。对于供应商和消费者/生产消费者来说,最优的DG (ODG)分配和规模一直是一个挑战。ODG的基本目标是通过降低功率损耗来提高系统的整体效率,最大限度地提高系统的安全性、电压稳定性和可靠性。本文提出了灰太狼算法(Grey Wolf, GWO)作为求解径向配电系统ODG的非线性元启发式优化算法的最新进展。优化的目标是降低径向系统的日功率损耗和电压波动百分比。通过考虑分步注入策略,将GWO应用于ieee69总线配电测试系统中实现多个dg。考虑了两种不同的情况:具有固定容量的普通DG向系统注入有功和无功功率,以及作为直流电池的光伏发电的时序输出。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimum Allocation and Sizing of Multi-Distributed Generations: Step-by-Step Injection
The demand for energy is increased by increasing global population and rapid developments in the current industry and modern lifestyle. It is a necessity to promote and modernize the control systems of the electrical network and move forward to the green and smart energy systems. The integration of the distributed generations (DGs) with the optimum capacity and position is one of the viable keys for reducing the active and reactive power losses, providing standard system power quality, and also injecting more renewable energy sources into the system in order to extend decarbonized and green systems. The Optimal DG (ODG) allocation and sizing have always been challenging for both suppliers and consumers/prosumers. The fundamental objectives of ODG are to enhance system overall efficiency with reduced power losses, maximize system security, voltage stability, and reliability. This paper proposes the implementation of the Grey Wolf (GWO) as state of the art for the nonlinear meta-heuristic optimization algorithm to solve ODG in the radial distribution system. The optimization aims are to reduce the percentage of daily power losses and voltage fluctuation of the radial systems. The GWO is applied to implement multiple DGs, by considering step-by-step injection strategy, to the IEEE 69 bus distribution test system. Two different scenarios are taking into account: the common DG with the fixed capacity to inject both active and reactive power to the system and time-series output for a photovoltaic generation which considered as a DC-battery.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信