Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Data-Driven Power Electronic Converter Modeling for Low Inertia Power
  System Dynamic Studies   A significant amount of converter-based generation is being integrated into
the bulk electric power grid to fulfill the future electric demand through
renewable energy sources, such as wind and photovoltaic. The dynamics of
converter systems in the overall stability of the power system can no longer be
neglected as in the past. Numerous efforts have been made in the literature to
derive detailed dynamic models, but using detailed models becomes complicated
and computationally prohibitive in large system level studies. In this paper,
we use a data-driven, black-box approach to model the dynamics of a power
electronic converter. System identification tools are used to identify the
dynamic models, while a power amplifier controlled by a real-time digital
simulator is used to perturb and control the converter. A set of linear dynamic
models for the converter are derived, which can be employed for system level
studies of converter-dominated electric grids.

10
The categories of this paper are: q-bio
8
The categories of this paper are: hep-ex
7
The categories of this paper are: hep-th
0
The categories of this paper are: hep-ph
26
The categories of this paper are: bayes-an
36
The categories of this paper are: cmp-lg
9
The categories of this paper are: nlin
33
The categories of this paper are: plasm-ph
11
The categories of this paper are: hep-lat
37
The categories of this paper are: supr-con
13
The categories of this paper are: quant-ph
14
The categories of this paper are: math-ph
29
The categories of this paper are: funct-an
32
The categories of this paper are: atom-ph
22
The categories of this paper are: chao-dyn
21
The categories of this paper are: adap-org