{"title":"An Efficient Method to Estimate Admittance of Black-boxed Inverter-based Resources for Varying Operating Points","authors":"Weihua Zhou;Bin Liu;Nabil Mohammed;Behrooz Bahrani","doi":"10.17775/CSEEJPES.2023.07090","DOIUrl":null,"url":null,"abstract":"Traditional analytical approaches for stability assessment of inverter-based resources (IBRs), often requiring detailed knowledge of IBR internals, become impractical due to IBRs' proprietary nature. Admittance measurements, relying on electromagnetic transient simulation or laboratory settings, are not only time-intensive but also operationally inflexible, since various non-linear control loops make IBRs' admittance models operating-point dependent. Therefore, such admittance measurements must be performed repeatedly when operating point changes. To avoid time-consuming and cumbersome measurements, admittance estimation for arbitrary operating points is highly desirable. However, existing admittance estimation algorithms usually face challenges in versatility, data demands, and accuracy. Addressing this challenge, this letter presents a simple and efficient admittance estimation method for black-boxed IBRs, by utilizing a minimal set of seven operating points to solve a homogeneous linear equation system. Case studies demonstrate this proposed method ensures high accuracy across various types of IBRs. Estimation accuracy is satisfying even when non-negligible measurement errors exist.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":null,"pages":null},"PeriodicalIF":6.9000,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10376018","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"CSEE Journal of Power and Energy Systems","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10376018/","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
Traditional analytical approaches for stability assessment of inverter-based resources (IBRs), often requiring detailed knowledge of IBR internals, become impractical due to IBRs' proprietary nature. Admittance measurements, relying on electromagnetic transient simulation or laboratory settings, are not only time-intensive but also operationally inflexible, since various non-linear control loops make IBRs' admittance models operating-point dependent. Therefore, such admittance measurements must be performed repeatedly when operating point changes. To avoid time-consuming and cumbersome measurements, admittance estimation for arbitrary operating points is highly desirable. However, existing admittance estimation algorithms usually face challenges in versatility, data demands, and accuracy. Addressing this challenge, this letter presents a simple and efficient admittance estimation method for black-boxed IBRs, by utilizing a minimal set of seven operating points to solve a homogeneous linear equation system. Case studies demonstrate this proposed method ensures high accuracy across various types of IBRs. Estimation accuracy is satisfying even when non-negligible measurement errors exist.
期刊介绍:
The CSEE Journal of Power and Energy Systems (JPES) is an international bimonthly journal published by the Chinese Society for Electrical Engineering (CSEE) in collaboration with CEPRI (China Electric Power Research Institute) and IEEE (The Institute of Electrical and Electronics Engineers) Inc. Indexed by SCI, Scopus, INSPEC, CSAD (Chinese Science Abstracts Database), DOAJ, and ProQuest, it serves as a platform for reporting cutting-edge theories, methods, technologies, and applications shaping the development of power systems in energy transition. The journal offers authors an international platform to enhance the reach and impact of their contributions.