DSM in Forecasting and Scheduling for Improving Integration of Renewable Energy Generation to the Grid

P. Saikishan Bharadwaj, R. Kannan, H. Sridevi
{"title":"DSM in Forecasting and Scheduling for Improving Integration of Renewable Energy Generation to the Grid","authors":"P. Saikishan Bharadwaj, R. Kannan, H. Sridevi","doi":"10.1109/RTEICT46194.2019.9016753","DOIUrl":null,"url":null,"abstract":"The integration of renewable energy into the grid has become a challenge and faces two fundamental technological problems, namely variability and location. As renewable resources are focused far from the customers, it requires extra-long length, high-capacity transmission to coordinate the supply with the demand. It is essential to recognize the fluctuation and the vulnerability when examining and anticipating the tasks of the power grid. The test of the changeability can be met by exchanging conventional generation goal in or out in response to the possible estimates of weather by forecast and schedule deviation settlement mechanism (DSM). The deviation settlement mechanism is a penalty to the generator who under injects or over injects power into or outside the state with a buffer limit to bring awareness to the generator so that the forecast generation almost meets the actual generation taking the accuracy & AvC into account, in this paper the DSM calculations for inter and intra state has been shown and the comparison between less and more deviation pattern is shown for both solar and wind substations.","PeriodicalId":269385,"journal":{"name":"2019 4th International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 4th International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTEICT46194.2019.9016753","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

The integration of renewable energy into the grid has become a challenge and faces two fundamental technological problems, namely variability and location. As renewable resources are focused far from the customers, it requires extra-long length, high-capacity transmission to coordinate the supply with the demand. It is essential to recognize the fluctuation and the vulnerability when examining and anticipating the tasks of the power grid. The test of the changeability can be met by exchanging conventional generation goal in or out in response to the possible estimates of weather by forecast and schedule deviation settlement mechanism (DSM). The deviation settlement mechanism is a penalty to the generator who under injects or over injects power into or outside the state with a buffer limit to bring awareness to the generator so that the forecast generation almost meets the actual generation taking the accuracy & AvC into account, in this paper the DSM calculations for inter and intra state has been shown and the comparison between less and more deviation pattern is shown for both solar and wind substations.
DSM在可再生能源发电并网预测与调度中的应用
可再生能源并网已成为一个挑战,面临两个基本的技术问题,即可变性和位置。由于可再生资源的重点远离用户,因此需要超长长度、大容量的输电来协调供需。在检查和预测电网的任务时,必须认识到电网的波动性和脆弱性。根据天气预报和调度偏差结算机制(DSM)对天气的可能估计,可通过交换常规发电目标来满足变异性的测试。偏差补偿机制是对处于缓冲限制状态或状态外的欠注或超注发电机组的一种惩罚,使发电机组意识到,在考虑精度和AvC的情况下,预测发电量与实际发电量基本一致。本文给出了状态间和状态内的DSM计算,并对太阳能和风能变电站的偏差模式进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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:481959085
Book学术官方微信