Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning from power system data stream: phasor-detective approach   Assuming access to synchronized stream of Phasor Measurement Unit (PMU) data
over a significant portion of a power system interconnect, say controlled by an
Independent System Operator (ISO), what can you extract about past, current and
future state of the system? We have focused on answering this practical
questions pragmatically - empowered with nothing but standard tools of data
analysis, such as PCA, filtering and cross-correlation analysis. Quite
surprisingly we have found that even during the quiet "no significant events"
period this standard set of statistical tools allows the "phasor-detective" to
extract from the data important hidden anomalies, such as problematic control
loops at loads and wind farms, and mildly malfunctioning assets, such as
transformers and generators. We also discuss and sketch future challenges a
mature phasor-detective can possibly tackle by adding machine learning and
physics modeling sophistication to the basic approach.

5
The categories of this paper are: gr-qc
25
The categories of this paper are: patt-sol
20
The categories of this paper are: acc-phys
7
The categories of this paper are: hep-th
18
The categories of this paper are: econ
13
The categories of this paper are: quant-ph
30
The categories of this paper are: q-alg
22
The categories of this paper are: chao-dyn
35
The categories of this paper are: mtrl-th
28
The categories of this paper are: alg-geom
33
The categories of this paper are: plasm-ph
23
The categories of this paper are: solv-int
1
The categories of this paper are: cs
16
The categories of this paper are: stat
37
The categories of this paper are: supr-con
26
The categories of this paper are: bayes-an