Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Data-Driven Time Series Reconstruction for Modern Power Systems Research   A critical aspect of power systems research is the availability of suitable
data, access to which is limited by privacy concerns and the sensitive nature
of energy infrastructure. This lack of data, in turn, hinders the development
of modern research avenues such as machine learning approaches or stochastic
formulations. To overcome this challenge, this paper proposes a systematic,
data-driven framework for reconstructing high-fidelity time series, using
publicly-available grid snapshots and historical data published by transmission
system operators. The proposed approach, from geo-spatial data and generation
capacity reconstruction, to time series disaggregation, is applied to the
French transmission grid. Thereby, synthetic but highly realistic time series
data, spanning multiple years with a 5-minute granularity, is generated at the
individual component level.

29
The categories of this paper are: funct-an
24
The categories of this paper are: dg-ga
35
The categories of this paper are: mtrl-th
31
The categories of this paper are: ao-sci
8
The categories of this paper are: hep-ex
13
The categories of this paper are: quant-ph
28
The categories of this paper are: alg-geom
3
The categories of this paper are: physics
33
The categories of this paper are: plasm-ph
6
The categories of this paper are: astro-ph
11
The categories of this paper are: hep-lat
5
The categories of this paper are: gr-qc
32
The categories of this paper are: atom-ph
34
The categories of this paper are: chem-ph
0
The categories of this paper are: hep-ph
16
The categories of this paper are: stat