结构时间序列模型的短期动能预测——以北欧电力系统为例

F. Gonzalez-Longatt, M. Acosta, H. Chamorro, D. Topić
{"title":"结构时间序列模型的短期动能预测——以北欧电力系统为例","authors":"F. Gonzalez-Longatt, M. Acosta, H. Chamorro, D. Topić","doi":"10.1109/SST49455.2020.9264087","DOIUrl":null,"url":null,"abstract":"Modern power systems are experiencing a gradual substitution of the classical synchronous generators by power electronic-based technologies; as a consequence, there is an increased interested in estimating the total rotating inertia. This paper proposes the use of the decomposable time series model to short term forecast of the total kinetic energy (KE) of a power system. The structure of the forecasting model includes three main components: trend, a seasonal and an irregular component. As the Nordic Power System (NPS) is expected a reduction of the total kinetic energy, this paper uses a time series of KE to test the proposed approach. A cross-validation process is used in this paper, numerical results of the mean absolute percentage error indicate forecast the error in the forecasting is below 5% for predictions one hour into the future.","PeriodicalId":284895,"journal":{"name":"2020 International Conference on Smart Systems and Technologies (SST)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Short-term Kinetic Energy Forecast using a Structural Time Series Model: Study Case of Nordic Power System\",\"authors\":\"F. Gonzalez-Longatt, M. Acosta, H. Chamorro, D. Topić\",\"doi\":\"10.1109/SST49455.2020.9264087\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Modern power systems are experiencing a gradual substitution of the classical synchronous generators by power electronic-based technologies; as a consequence, there is an increased interested in estimating the total rotating inertia. This paper proposes the use of the decomposable time series model to short term forecast of the total kinetic energy (KE) of a power system. The structure of the forecasting model includes three main components: trend, a seasonal and an irregular component. As the Nordic Power System (NPS) is expected a reduction of the total kinetic energy, this paper uses a time series of KE to test the proposed approach. A cross-validation process is used in this paper, numerical results of the mean absolute percentage error indicate forecast the error in the forecasting is below 5% for predictions one hour into the future.\",\"PeriodicalId\":284895,\"journal\":{\"name\":\"2020 International Conference on Smart Systems and Technologies (SST)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Smart Systems and Technologies (SST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SST49455.2020.9264087\",\"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 International Conference on Smart Systems and Technologies (SST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SST49455.2020.9264087","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12

摘要

现代电力系统正逐渐被电力电子技术所取代;因此,人们对估计总的旋转惯量越来越感兴趣。本文提出将可分解时间序列模型用于电力系统总动能的短期预测。预测模型的结构包括三个主要成分:趋势成分、季节性成分和不规则成分。由于北欧电力系统(NPS)期望降低总动能,本文使用KE的时间序列来测试所提出的方法。本文采用交叉验证方法,平均绝对百分比误差的数值结果表明,对未来1小时的预测误差在5%以下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Short-term Kinetic Energy Forecast using a Structural Time Series Model: Study Case of Nordic Power System
Modern power systems are experiencing a gradual substitution of the classical synchronous generators by power electronic-based technologies; as a consequence, there is an increased interested in estimating the total rotating inertia. This paper proposes the use of the decomposable time series model to short term forecast of the total kinetic energy (KE) of a power system. The structure of the forecasting model includes three main components: trend, a seasonal and an irregular component. As the Nordic Power System (NPS) is expected a reduction of the total kinetic energy, this paper uses a time series of KE to test the proposed approach. A cross-validation process is used in this paper, numerical results of the mean absolute percentage error indicate forecast the error in the forecasting is below 5% for predictions one hour into the future.
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