Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Understanding the Safety Requirements for Learning-based Power Systems
  Operations   Recent advancements in machine learning and reinforcement learning have
brought increased attention to their applicability in a range of
decision-making tasks in the operations of power systems, such as short-term
emergency control, Volt/VAr control, long-term residential demand response and
battery energy management. Despite the promises of providing strong
representation of complex system dynamics and fast, efficient learned operation
strategies, the safety requirements of such learning paradigms are less
discussed. This paper explores the design requirements on both data and model
side of such learning algorithms by exploiting the impacts of adversarial
attacks on safety critical system operations. Case studies performed on both
voltage regulation and topology control tasks demonstrated the potential
vulnerabilities of the standard reinforcement learning algorithms, and possible
measures of machine learning robustness and security are discussed for power
systems operation tasks.

6
The categories of this paper are: astro-ph
36
The categories of this paper are: cmp-lg
29
The categories of this paper are: funct-an
31
The categories of this paper are: ao-sci
35
The categories of this paper are: mtrl-th
3
The categories of this paper are: physics
10
The categories of this paper are: q-bio
30
The categories of this paper are: q-alg
37
The categories of this paper are: supr-con
12
The categories of this paper are: nucl-th
18
The categories of this paper are: econ
4
The categories of this paper are: cond-mat
21
The categories of this paper are: adap-org
34
The categories of this paper are: chem-ph
22
The categories of this paper are: chao-dyn
15
The categories of this paper are: nucl-ex