Di Wu, Hui Liu, Wei-Hsin Peng, Longzhen Yu, Lin Shi, Yiping Yu
{"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}
引用次数: 0
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.