多维电力系统仿真自适应时间模式的发展

D. vom Stein, N. van Bracht, A. Maaz, A. Moser
{"title":"多维电力系统仿真自适应时间模式的发展","authors":"D. vom Stein, N. van Bracht, A. Maaz, A. Moser","doi":"10.1109/EEM.2017.7981868","DOIUrl":null,"url":null,"abstract":"The changes in the European power system come with the necessity of modeling the power system in high detail. Especially, when applying stochastic simulation approaches this leads to increasing problem sizes. In this work, we introduce a methodology to reduce the size of optimization problems in the temporal dimension to achieve lower computation times. The method is based on a mixed-integer optimization reducing the modeled time intervals that can be applied to a wide variety of optimization problems. The potential of the approach is proven by a linear unit dispatch problem for the European power system in the year 2024. The comparison of an equidistant and predefined time pattern with the preceding optimization of an adaptive time pattern shows improvements in accuracy regarding the deviation in yearly power generation, which range between 20 % and 25 %, without increasing computational requirements regarding time or hardware.","PeriodicalId":416082,"journal":{"name":"2017 14th International Conference on the European Energy Market (EEM)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Development of adaptive time patterns for multi-dimensional power system simulations\",\"authors\":\"D. vom Stein, N. van Bracht, A. Maaz, A. Moser\",\"doi\":\"10.1109/EEM.2017.7981868\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The changes in the European power system come with the necessity of modeling the power system in high detail. Especially, when applying stochastic simulation approaches this leads to increasing problem sizes. In this work, we introduce a methodology to reduce the size of optimization problems in the temporal dimension to achieve lower computation times. The method is based on a mixed-integer optimization reducing the modeled time intervals that can be applied to a wide variety of optimization problems. The potential of the approach is proven by a linear unit dispatch problem for the European power system in the year 2024. The comparison of an equidistant and predefined time pattern with the preceding optimization of an adaptive time pattern shows improvements in accuracy regarding the deviation in yearly power generation, which range between 20 % and 25 %, without increasing computational requirements regarding time or hardware.\",\"PeriodicalId\":416082,\"journal\":{\"name\":\"2017 14th International Conference on the European Energy Market (EEM)\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 14th International Conference on the European Energy Market (EEM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EEM.2017.7981868\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 14th International Conference on the European Energy Market (EEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EEM.2017.7981868","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13

摘要

欧洲电力系统的变化带来了对电力系统进行详细建模的必要性。特别是,当应用随机模拟方法时,这会导致问题规模的增加。在这项工作中,我们引入了一种在时间维度上减少优化问题大小的方法,以实现更低的计算时间。该方法基于混合整数优化,减少了建模时间间隔,可应用于各种优化问题。2024年欧洲电力系统线性机组调度问题证明了该方法的潜力。等距和预定义的时间模式与前面的自适应时间模式优化的比较表明,在不增加关于时间或硬件的计算需求的情况下,关于年发电量偏差的准确性得到了提高,偏差范围在20%到25%之间。
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
Development of adaptive time patterns for multi-dimensional power system simulations
The changes in the European power system come with the necessity of modeling the power system in high detail. Especially, when applying stochastic simulation approaches this leads to increasing problem sizes. In this work, we introduce a methodology to reduce the size of optimization problems in the temporal dimension to achieve lower computation times. The method is based on a mixed-integer optimization reducing the modeled time intervals that can be applied to a wide variety of optimization problems. The potential of the approach is proven by a linear unit dispatch problem for the European power system in the year 2024. The comparison of an equidistant and predefined time pattern with the preceding optimization of an adaptive time pattern shows improvements in accuracy regarding the deviation in yearly power generation, which range between 20 % and 25 %, without increasing computational requirements regarding time or hardware.
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
Market integration VS temporal granularity: How to provide needed flexibility resources? FV-battery community energy systems: Economic, energy independence and network deferral analysis Adequacy of power capacity during winter peaks in Finland An analysis of market mechanism and bidding strategy for power balancing market mixed by conventional and renewable energy Network pricing for smart grids considering customers' diversified contribution to system
×
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