基于混合交叉连续蚁群优化的有效电力调度

Z. Hamid, I. Musirin, M. Rahim, N. A. M. Kamari
{"title":"基于混合交叉连续蚁群优化的有效电力调度","authors":"Z. Hamid, I. Musirin, M. Rahim, N. A. M. Kamari","doi":"10.1109/ICTKE.2012.6152415","DOIUrl":null,"url":null,"abstract":"A new method to select suitable generators for the purpose of power scheduling has been proposed in this paper, namely Fast Voltage Stability Index Generation Tracing (FVSI-GT). Contrary to previous power tracing techniques which select the generators based on the magnitude of traced power, the proposed technique performs the generator selection based on the stability index contributed by individual system's generator. After tracing the contributed stability index, the sizing process of generators' power to be dispatched has been performed via a new hybrid optimization algorithm; Blended Crossover Continuous Ant Colony Optimization (BX-CACO). From experiment and validation on IEEE 30 bus reliability test system (RTS), it is revealed that FVSI-GT exhibits great performance as the method capable to select exact generators with the enhancement of system's static stability, losses and fuel cost minimization with fast optimization via BX-CACO.","PeriodicalId":235347,"journal":{"name":"2011 Ninth International Conference on ICT and Knowledge Engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Effective power scheduling via Blended Crossover Continuous Ant Colony Optimization\",\"authors\":\"Z. Hamid, I. Musirin, M. Rahim, N. A. M. Kamari\",\"doi\":\"10.1109/ICTKE.2012.6152415\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new method to select suitable generators for the purpose of power scheduling has been proposed in this paper, namely Fast Voltage Stability Index Generation Tracing (FVSI-GT). Contrary to previous power tracing techniques which select the generators based on the magnitude of traced power, the proposed technique performs the generator selection based on the stability index contributed by individual system's generator. After tracing the contributed stability index, the sizing process of generators' power to be dispatched has been performed via a new hybrid optimization algorithm; Blended Crossover Continuous Ant Colony Optimization (BX-CACO). From experiment and validation on IEEE 30 bus reliability test system (RTS), it is revealed that FVSI-GT exhibits great performance as the method capable to select exact generators with the enhancement of system's static stability, losses and fuel cost minimization with fast optimization via BX-CACO.\",\"PeriodicalId\":235347,\"journal\":{\"name\":\"2011 Ninth International Conference on ICT and Knowledge Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-02-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Ninth International Conference on ICT and Knowledge Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICTKE.2012.6152415\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Ninth International Conference on ICT and Knowledge Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTKE.2012.6152415","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

本文提出了一种以电力调度为目的选择合适发电机的新方法——快速电压稳定指数发电跟踪(FVSI-GT)。与以往基于跟踪功率大小选择发电机的电力跟踪技术不同,该技术基于单个系统发电机贡献的稳定性指标进行发电机选择。在对贡献的稳定指标进行跟踪后,通过一种新的混合优化算法进行发电机待调度功率的确定过程;混合交叉连续蚁群优化(BX-CACO)。在IEEE 30总线可靠性测试系统(RTS)上的实验和验证表明,FVSI-GT方法具有良好的性能,可以通过BX-CACO快速优化,提高系统的静态稳定性、损耗和燃料成本最小化。
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
Effective power scheduling via Blended Crossover Continuous Ant Colony Optimization
A new method to select suitable generators for the purpose of power scheduling has been proposed in this paper, namely Fast Voltage Stability Index Generation Tracing (FVSI-GT). Contrary to previous power tracing techniques which select the generators based on the magnitude of traced power, the proposed technique performs the generator selection based on the stability index contributed by individual system's generator. After tracing the contributed stability index, the sizing process of generators' power to be dispatched has been performed via a new hybrid optimization algorithm; Blended Crossover Continuous Ant Colony Optimization (BX-CACO). From experiment and validation on IEEE 30 bus reliability test system (RTS), it is revealed that FVSI-GT exhibits great performance as the method capable to select exact generators with the enhancement of system's static stability, losses and fuel cost minimization with fast optimization via BX-CACO.
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
Development of object detection software for a mobile robot using an AForce.Net framework Hybrid parallel approach based on wavelet transformation and principle component analysis for solving face recognition problem Developing an influence diagram using a Structural Modeling, Inference, and Learning Engine A mixed integer non-linear programming model for optimizing the collection methods of returned products Towards a data warehouse testing framework
×
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