基于混合元启发式方法的分布式发电优化规划

Kundan Kumar, Ramswaroop Ramswaroop, L. Yadav, Puneet Joshi, Medha Joshi
{"title":"基于混合元启发式方法的分布式发电优化规划","authors":"Kundan Kumar, Ramswaroop Ramswaroop, L. Yadav, Puneet Joshi, Medha Joshi","doi":"10.1109/PIICON49524.2020.9112955","DOIUrl":null,"url":null,"abstract":"RES based DGs have gained popularity due to depletion of fossil reserves, increase demand (i.e. industrial growth, urbanization etc.). DG comprises of low generating capacity units installed near load dispatch centers. To provide the necessary active power RESs are also employed for providing reactive power support but it greatly varies with the type of DG units. That is why DGs are characterized in four major types based on real & imaginary power delivery capability. Installing an appropriate capacity at the most suitable bus is a nonlinear & nonconvex optimization problem. When optimally sited & sized RES minimize Preal loss & also improve voltage profile of the network. This artificial process hybrid of Particle Swarm Optimization (PSO) algorithm and Grey Wolf Optimization (GWO) algorithm for optimum allocating and sizing of Type-1 & Type- 2 DGs. This hybrid approach is applied and tested on IEEE 33 & IEEE 69 bus to achieve power loss minimization.","PeriodicalId":422853,"journal":{"name":"2020 IEEE 9th Power India International Conference (PIICON)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimal Planning of Distributed Generation using Hybrid Metaheuristic Approach\",\"authors\":\"Kundan Kumar, Ramswaroop Ramswaroop, L. Yadav, Puneet Joshi, Medha Joshi\",\"doi\":\"10.1109/PIICON49524.2020.9112955\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"RES based DGs have gained popularity due to depletion of fossil reserves, increase demand (i.e. industrial growth, urbanization etc.). DG comprises of low generating capacity units installed near load dispatch centers. To provide the necessary active power RESs are also employed for providing reactive power support but it greatly varies with the type of DG units. That is why DGs are characterized in four major types based on real & imaginary power delivery capability. Installing an appropriate capacity at the most suitable bus is a nonlinear & nonconvex optimization problem. When optimally sited & sized RES minimize Preal loss & also improve voltage profile of the network. This artificial process hybrid of Particle Swarm Optimization (PSO) algorithm and Grey Wolf Optimization (GWO) algorithm for optimum allocating and sizing of Type-1 & Type- 2 DGs. This hybrid approach is applied and tested on IEEE 33 & IEEE 69 bus to achieve power loss minimization.\",\"PeriodicalId\":422853,\"journal\":{\"name\":\"2020 IEEE 9th Power India International Conference (PIICON)\",\"volume\":\"110 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 9th Power India International Conference (PIICON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PIICON49524.2020.9112955\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 9th Power India International Conference (PIICON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PIICON49524.2020.9112955","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

由于化石储量的枯竭、需求的增加(即工业增长、城市化等),基于可再生能源的DGs越来越受欢迎。DG由安装在负荷调度中心附近的低发电容量机组组成。为了提供必要的有功功率,也采用RESs来提供无功功率支持,但随DG机组的类型而有很大差异。这就是为什么dg根据实际和假想的电力输送能力分为四种主要类型。在最合适的母线上设置合适的容量是一个非线性非凸优化问题。当最佳位置和大小的RES最大限度地减少Preal损耗,也改善了网络的电压分布。本文将粒子群优化算法(PSO)与灰狼优化算法(GWO)相结合,对1型和2型dg进行优化分配和分级。该方法在ieee33和ieee69总线上进行了应用和测试,实现了功耗最小化。
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
Optimal Planning of Distributed Generation using Hybrid Metaheuristic Approach
RES based DGs have gained popularity due to depletion of fossil reserves, increase demand (i.e. industrial growth, urbanization etc.). DG comprises of low generating capacity units installed near load dispatch centers. To provide the necessary active power RESs are also employed for providing reactive power support but it greatly varies with the type of DG units. That is why DGs are characterized in four major types based on real & imaginary power delivery capability. Installing an appropriate capacity at the most suitable bus is a nonlinear & nonconvex optimization problem. When optimally sited & sized RES minimize Preal loss & also improve voltage profile of the network. This artificial process hybrid of Particle Swarm Optimization (PSO) algorithm and Grey Wolf Optimization (GWO) algorithm for optimum allocating and sizing of Type-1 & Type- 2 DGs. This hybrid approach is applied and tested on IEEE 33 & IEEE 69 bus to achieve power loss minimization.
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
An Improved Grid Synchronization Method of Grid-Interactive Power Converter System During Distorted Grid Conditions Design and Implementation of Biquad Filter for Shunt Compensation under Normal and Distorted Grid Conditions High Voltage Gain DC-DC Non-Isolated Converter with Generalized Stages Irregular-shaped Particle Motion and Charge Transfer Mechanism in Transformer Oil under Varying Field Reduce, Recycle And Reuse First Ever Initiative By Any Haryana Govt. Power Utility And Its Outcomes
×
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