Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Component Outage Estimation based on Support Vector Machine   Predicting power system component outages in response to an imminent
hurricane plays a major role in preevent planning and post-event recovery of
the power system. An exact prediction of components states, however, is a
challenging task and cannot be easily performed. In this paper, a Support
Vector Machine (SVM) based method is proposed to help estimate the components
states in response to anticipated path and intensity of an imminent hurricane.
Components states are categorized into three classes of damaged, operational,
and uncertain. The damaged components along with the components in uncertain
class are then considered in multiple contingency scenarios of a proposed
Event-driven Security-Constrained Unit Commitment (E-SCUC), which considers the
simultaneous outage of multiple components under an N-m-u reliability
criterion. Experimental results on the IEEE 118-bus test system show the merits
and the effectiveness of the proposed SVM classifier and the E-SCUC model in
improving power system resilience in response to extreme events.

30
The categories of this paper are: q-alg
4
The categories of this paper are: cond-mat
2
The categories of this paper are: math
23
The categories of this paper are: solv-int
8
The categories of this paper are: hep-ex
31
The categories of this paper are: ao-sci
37
The categories of this paper are: supr-con
19
The categories of this paper are: eess
29
The categories of this paper are: funct-an
13
The categories of this paper are: quant-ph
28
The categories of this paper are: alg-geom
5
The categories of this paper are: gr-qc
21
The categories of this paper are: adap-org
32
The categories of this paper are: atom-ph
18
The categories of this paper are: econ
22
The categories of this paper are: chao-dyn