A System Identification-based Modeling Framework of Bidirectional DC-DC Converters for Power Grids

作     者：Gabriel E.Mejia-Ruiz Mario R.A.Paternina Juan R.Rodriguez R. Juan M.Ramirez Alejandro Zamora-Mendez Guillermo Bolivar-O. Gabriel E.Mejia-Ruiz;Mario R.A.Paternina;Juan R.Rodriguez R.;Juan M.Ramirez;Alejandro Zamora-Mendez;Guillermo Bolivar-O.

作者机构：Department of Electrical EngineeringNational Autonomous University of Mexico(UNAM)Mexico CityMexico Department of Electrical EngineeringCenter for Research and Advanced Studies(CINVESTAV)GuadalajaraMexico Electrical Engineering FacultyMichoacan University of Saint Nicholas of Hidalgo(UMSNH)MoreliaMexico Engineering FacultyCorporacion Universitaria Minuto de Dios-UNIMINUTOBelloColombia 

出 版 物：《Journal of Modern Power Systems and Clean Energy》 (现代电力系统与清洁能源学报（英文）)

年 卷 期：2022年第10卷第3期

页      面：788-799页

核心收录：

学科分类：080801[工学-电机与电器] 0808[工学-电气工程] 08[工学] 

基　　金：supported by the Project Support Program for Research and Technological Innovation of UNAM(DGAPA,PAPIIT-2021)(No.TA101421) the strategic project PE-A-04 of CEMIE-Redes。 

主　　题：Dual active bridge eigensystem realization algorithm generalized average model power electronic converter identification 

摘      要：This paper proposes a system identification framework based on eigensystem realization to accurately model power electronic converters.The proposed framework affords an energy-based optimal reduction method to precisely identify the dynamics of power electronic converters from simulated or actual raw data measured at the converter’s ports.This method does not require any prior knowledge of the topology or internal parameters of the converter to derive the system modal information.The accuracy and feasibility of the proposed method are exhaustively evaluated via simulations and practical tests on a software-simulated and hardware-implemented dual active bridge(DAB)converter under steady-state and transient conditions.After various comparisons with the Fourier series-based generalized average model,switching model,and experimental measurements,the proposed method attains a root mean square error(RMSE)of less than 1%with respect to the actual raw data.Moreover,the computational effort is reduced to 1/8.6 of the Fourier series-based model.