基于ARMAX模型的电力系统惯性辨识

Di Wu, Hui Liu, Wei-Hsin Peng, Longzhen Yu, Lin Shi, Yiping Yu
{"title":"基于ARMAX模型的电力系统惯性辨识","authors":"Di Wu, Hui Liu, Wei-Hsin Peng, Longzhen Yu, Lin Shi, Yiping Yu","doi":"10.1109/AEEES56888.2023.10114228","DOIUrl":null,"url":null,"abstract":"Under the background of double carbon strategy goal, the development prospect of wind power is very broad because of its advantages such as low cost and easy expansion. However, wind power output has strong random volatility, and large-scale wind turbine connected to the power grid through power electronic devices will not actively respond to changes in external frequency. The inertia stored in the rotor is difficult to provide inertia support for the system, resulting in a decline in the overall inertia level of the system, which further reduces the anti-disturbance ability and threatens the stability of the system frequency. In this paper, an online identification method of inertia of power system based on ARMAX model is proposed. The accuracy of this identification method is verified by comparing the inertia of motor and doubly-fed wind turbine under pulse disturbance and step disturbance. This method does not need to apply large disturbance and has higher security.","PeriodicalId":272114,"journal":{"name":"2023 5th Asia Energy and Electrical Engineering Symposium (AEEES)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Inertia Identification of Power System Based on ARMAX Model\",\"authors\":\"Di Wu, Hui Liu, Wei-Hsin Peng, Longzhen Yu, Lin Shi, Yiping Yu\",\"doi\":\"10.1109/AEEES56888.2023.10114228\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Under the background of double carbon strategy goal, the development prospect of wind power is very broad because of its advantages such as low cost and easy expansion. However, wind power output has strong random volatility, and large-scale wind turbine connected to the power grid through power electronic devices will not actively respond to changes in external frequency. The inertia stored in the rotor is difficult to provide inertia support for the system, resulting in a decline in the overall inertia level of the system, which further reduces the anti-disturbance ability and threatens the stability of the system frequency. In this paper, an online identification method of inertia of power system based on ARMAX model is proposed. The accuracy of this identification method is verified by comparing the inertia of motor and doubly-fed wind turbine under pulse disturbance and step disturbance. This method does not need to apply large disturbance and has higher security.\",\"PeriodicalId\":272114,\"journal\":{\"name\":\"2023 5th Asia Energy and Electrical Engineering Symposium (AEEES)\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 5th Asia Energy and Electrical Engineering Symposium (AEEES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AEEES56888.2023.10114228\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 5th Asia Energy and Electrical Engineering Symposium (AEEES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AEEES56888.2023.10114228","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

在双碳战略目标背景下,风电因其成本低、易于扩容等优势,发展前景十分广阔。然而,风电输出具有较强的随机波动性,通过电力电子设备接入电网的大型风力发电机组不会主动响应外界频率的变化。转子中储存的惯性难以为系统提供惯性支撑,导致系统整体惯性水平下降,进一步降低了系统的抗干扰能力,威胁到系统频率的稳定性。提出了一种基于ARMAX模型的电力系统惯性在线辨识方法。通过对比电机和双馈风力机在脉冲扰动和阶跃扰动下的惯量,验证了该辨识方法的准确性。该方法不需要施加较大的干扰,具有较高的安全性。
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
Inertia Identification of Power System Based on ARMAX Model
Under the background of double carbon strategy goal, the development prospect of wind power is very broad because of its advantages such as low cost and easy expansion. However, wind power output has strong random volatility, and large-scale wind turbine connected to the power grid through power electronic devices will not actively respond to changes in external frequency. The inertia stored in the rotor is difficult to provide inertia support for the system, resulting in a decline in the overall inertia level of the system, which further reduces the anti-disturbance ability and threatens the stability of the system frequency. In this paper, an online identification method of inertia of power system based on ARMAX model is proposed. The accuracy of this identification method is verified by comparing the inertia of motor and doubly-fed wind turbine under pulse disturbance and step disturbance. This method does not need to apply large disturbance and has higher security.
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
Optimization of High Speed Permanent Magnet Synchronous Motor Based on Co-simulation Method Multi-objective Hierarchical Optimal Scheduling of Microgrids with V2G Price Incentives Fast Intrusion Detection in High Voltage Zone of Electric Power Operations Based on YOLO and Homography Transformation Algorithm Stability Improvement Strategy of Distribution Network Based on Grid-Forming Mode Switching Time Series Based Co-optimization Model of Active and Reactive Power with PV-wind and Storage
×
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