重构环境下可再生能源与电动汽车问题的探讨

IF 1.5 Q4 ENERGY & FUELS
Amita Singh, Veena Sharma, Vineet Kumar, R. Naresh, O. P. Rahi, Vineet Kumar
{"title":"重构环境下可再生能源与电动汽车问题的探讨","authors":"Amita Singh, Veena Sharma, Vineet Kumar, R. Naresh, O. P. Rahi, Vineet Kumar","doi":"10.1177/0309524x231185492","DOIUrl":null,"url":null,"abstract":"This research proposes a novel solution for the optimal day-ahead scheduling problem in the GAMS environment using the BARON approach. The challenge is extended to include Renewable Energy Sources (RESs) and Electric Vehicles (EVs), making it more complex and practical. EVs serve as loads, energy suppliers, and storage during RESs’ uncertainties. The framework improves cost savings, quality, reliability, and stability of the power supply system by modeling solar, wind, and EV power in the scheduling problem. The solution is tested on a 10 -unit thermal system considering RESs and EVs under deterministic and stochastic environments. Stochastic scenarios are generated using Monte Carlo simulation, and the simultaneous scenario reduction approach enhances results. The BARON solver outperforms other solvers, achieving profits of $205,321 with wind, solar, and EVs, and $187,297 when considering uncertainty, resulting in a reduction of $18,024.","PeriodicalId":51570,"journal":{"name":"Wind Engineering","volume":"25 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2023-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Investigation of PBUC problem with RES and EV in restructured environment\",\"authors\":\"Amita Singh, Veena Sharma, Vineet Kumar, R. Naresh, O. P. Rahi, Vineet Kumar\",\"doi\":\"10.1177/0309524x231185492\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research proposes a novel solution for the optimal day-ahead scheduling problem in the GAMS environment using the BARON approach. The challenge is extended to include Renewable Energy Sources (RESs) and Electric Vehicles (EVs), making it more complex and practical. EVs serve as loads, energy suppliers, and storage during RESs’ uncertainties. The framework improves cost savings, quality, reliability, and stability of the power supply system by modeling solar, wind, and EV power in the scheduling problem. The solution is tested on a 10 -unit thermal system considering RESs and EVs under deterministic and stochastic environments. Stochastic scenarios are generated using Monte Carlo simulation, and the simultaneous scenario reduction approach enhances results. The BARON solver outperforms other solvers, achieving profits of $205,321 with wind, solar, and EVs, and $187,297 when considering uncertainty, resulting in a reduction of $18,024.\",\"PeriodicalId\":51570,\"journal\":{\"name\":\"Wind Engineering\",\"volume\":\"25 1\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2023-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Wind Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/0309524x231185492\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wind Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/0309524x231185492","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0

摘要

针对GAMS环境下的最优日前调度问题,提出了一种基于BARON方法的新解决方案。挑战扩展到可再生能源(RESs)和电动汽车(ev),使其更加复杂和实用。在RESs的不确定性期间,电动汽车充当负载、能源供应商和存储。该框架通过对太阳能、风能和电动汽车的调度问题进行建模,提高了供电系统的成本节约、质量、可靠性和稳定性。在确定性和随机环境下,对该方案进行了考虑RESs和ev的10单元热系统的测试。采用蒙特卡罗模拟方法生成随机场景,同时采用场景约简方法增强了结果。BARON求解器优于其他求解器,在考虑风能、太阳能和电动汽车的情况下实现了205,321美元的利润,在考虑不确定性时实现了187,297美元的利润,从而减少了18,024美元。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Investigation of PBUC problem with RES and EV in restructured environment
This research proposes a novel solution for the optimal day-ahead scheduling problem in the GAMS environment using the BARON approach. The challenge is extended to include Renewable Energy Sources (RESs) and Electric Vehicles (EVs), making it more complex and practical. EVs serve as loads, energy suppliers, and storage during RESs’ uncertainties. The framework improves cost savings, quality, reliability, and stability of the power supply system by modeling solar, wind, and EV power in the scheduling problem. The solution is tested on a 10 -unit thermal system considering RESs and EVs under deterministic and stochastic environments. Stochastic scenarios are generated using Monte Carlo simulation, and the simultaneous scenario reduction approach enhances results. The BARON solver outperforms other solvers, achieving profits of $205,321 with wind, solar, and EVs, and $187,297 when considering uncertainty, resulting in a reduction of $18,024.
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
Wind Engineering
Wind Engineering ENERGY & FUELS-
CiteScore
4.00
自引率
13.30%
发文量
81
期刊介绍: Having been in continuous publication since 1977, Wind Engineering is the oldest and most authoritative English language journal devoted entirely to the technology of wind energy. Under the direction of a distinguished editor and editorial board, Wind Engineering appears bimonthly with fully refereed contributions from active figures in the field, book notices, and summaries of the more interesting papers from other sources. Papers are published in Wind Engineering on: the aerodynamics of rotors and blades; machine subsystems and components; design; test programmes; power generation and transmission; measuring and recording techniques; installations and applications; and economic, environmental and legal aspects.
×
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:481959085
Book学术官方微信