太阳能电站配电网的优化重构

A. Bramm, S. Eroshenko
{"title":"太阳能电站配电网的优化重构","authors":"A. Bramm, S. Eroshenko","doi":"10.1109/USSEC53120.2021.9655718","DOIUrl":null,"url":null,"abstract":"The paper is concerned with the problem of determining the optimal reconfiguration of the power grid for each hour of the day. The optimization criterion is the value of the total power losses in the power grid. The considered network operates in parallel with a large power system and includes two solar power plants. Consumers in this network are represented by electricity load curve of three types. The technique for determining the optimal configuration is based on knowledge about the features of flow distribution in grids with renewable energy sources and the fundamental principles from the graph theory. Also, the method relies on the results of forecasting the generation of solar power plants connected to the considered power grid. Solar power plants’ forecasting is carried out by a decision tree model trained using machine learning methods. To train the predictive model, data on the generation of real solar power plants are used.","PeriodicalId":260032,"journal":{"name":"2021 Ural-Siberian Smart Energy Conference (USSEC)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimal Reconfiguration of Distribution Network with Solar Power Plants\",\"authors\":\"A. Bramm, S. Eroshenko\",\"doi\":\"10.1109/USSEC53120.2021.9655718\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper is concerned with the problem of determining the optimal reconfiguration of the power grid for each hour of the day. The optimization criterion is the value of the total power losses in the power grid. The considered network operates in parallel with a large power system and includes two solar power plants. Consumers in this network are represented by electricity load curve of three types. The technique for determining the optimal configuration is based on knowledge about the features of flow distribution in grids with renewable energy sources and the fundamental principles from the graph theory. Also, the method relies on the results of forecasting the generation of solar power plants connected to the considered power grid. Solar power plants’ forecasting is carried out by a decision tree model trained using machine learning methods. To train the predictive model, data on the generation of real solar power plants are used.\",\"PeriodicalId\":260032,\"journal\":{\"name\":\"2021 Ural-Siberian Smart Energy Conference (USSEC)\",\"volume\":\"118 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 Ural-Siberian Smart Energy Conference (USSEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/USSEC53120.2021.9655718\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Ural-Siberian Smart Energy Conference (USSEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/USSEC53120.2021.9655718","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

本文研究的是确定一天中每小时电网最优重构的问题。优化准则为电网的总损耗值。所考虑的网络与一个大型电力系统并行运行,包括两个太阳能发电厂。该网络中的用户用三种类型的电力负荷曲线表示。确定最优配置的技术是基于对可再生能源电网中流量分布特征的了解和图论的基本原理。此外,该方法依赖于对连接到考虑电网的太阳能发电厂的发电量的预测结果。太阳能发电厂的预测是通过使用机器学习方法训练的决策树模型进行的。为了训练预测模型,使用了真实太阳能发电厂的发电数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Reconfiguration of Distribution Network with Solar Power Plants
The paper is concerned with the problem of determining the optimal reconfiguration of the power grid for each hour of the day. The optimization criterion is the value of the total power losses in the power grid. The considered network operates in parallel with a large power system and includes two solar power plants. Consumers in this network are represented by electricity load curve of three types. The technique for determining the optimal configuration is based on knowledge about the features of flow distribution in grids with renewable energy sources and the fundamental principles from the graph theory. Also, the method relies on the results of forecasting the generation of solar power plants connected to the considered power grid. Solar power plants’ forecasting is carried out by a decision tree model trained using machine learning methods. To train the predictive model, data on the generation of real solar power plants are used.
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
×
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