2020/09/05 by Nischal Guruwacharya, Guruwacharya, Nischal, Niranjan Bhujel +13
Engineering · Physics and Astronomy · #FOS: Electrical engineering #Model Reduction and Neural Networks #Multilevel Inverters and Converters #Real-time simulation and control systems #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2009.02621
openalex publication_date 2020/09/05 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
A significant amount of converter-based generation is being integrated into\nthe bulk electric power grid to fulfill the future electric demand through\nrenewable energy sources, such as wind and photovoltaic. The dynamics of\nconverter systems in the overall stability of the power system can no longer be\nneglected as in the past. Numerous efforts have been made in the literature to\nderive detailed dynamic models, but using detailed models becomes complicated\nand computationally prohibitive in large system level studies. In this paper,\nwe use a data-driven, black-box approach to model the dynamics of a power\nelectronic converter. System identification tools are used to identify the\ndynamic models, while a power amplifier controlled by a real-time digital\nsimulator is used to perturb and control the converter. A set of linear dynamic\nmodels for the converter are derived, which can be employed for system level\nstudies of converter-dominated electric grids.\n