Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Data-Driven Security Assessment of the Electric Power System   The transition to a new low emission energy future results in a changing mix
of generation and load types due to significant growth in renewable energy
penetration and reduction in system inertia due to the exit of ageing fossil
fuel power plants. This increases technical challenges for electrical grid
planning and operation. This study introduces a new decomposition approach to
account for the system security for short term planning using conventional
machine learning tools. The immediate value of this work is that it provides
extendable and computationally efficient guidelines for using supervised
learning tools to assess first swing transient stability status. To provide an
unbiased evaluation of the final model fit on the training dataset, the
proposed approach was examined on a previously unseen test set. It
distinguished stable and unstable cases in the test set accurately, with only
0.57% error, and showed a high precision in predicting the time of instability,
with 6.8% error and mean absolute error as small as 0.0145.

15
The categories of this paper are: nucl-ex
34
The categories of this paper are: chem-ph
28
The categories of this paper are: alg-geom
18
The categories of this paper are: econ
22
The categories of this paper are: chao-dyn
29
The categories of this paper are: funct-an
27
The categories of this paper are: comp-gas
6
The categories of this paper are: astro-ph
24
The categories of this paper are: dg-ga
20
The categories of this paper are: acc-phys
37
The categories of this paper are: supr-con
3
The categories of this paper are: physics
33
The categories of this paper are: plasm-ph
17
The categories of this paper are: q-fin
23
The categories of this paper are: solv-int
32
The categories of this paper are: atom-ph