Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Influences in Forecast Errors for Wind and Photovoltaic Power: A Study
  on Machine Learning Models   Despite the increasing importance of forecasts of renewable energy, current
planning studies only address a general estimate of the forecast quality to be
expected and selected forecast horizons.
  However, these estimates allow only a limited and highly uncertain use in the
planning of electric power distribution. More reliable planning processes
require considerably more information about future forecast quality.
  In this article, we present an in-depth analysis and comparison of
influencing factors regarding uncertainty in wind and photovoltaic power
forecasts, based on four different machine learning (ML) models.
  In our analysis, we found substantial differences in uncertainty depending on
ML models, data coverage, and seasonal patterns that have to be considered in
future planning studies.

15
The categories of this paper are: nucl-ex
34
The categories of this paper are: chem-ph
22
The categories of this paper are: chao-dyn
9
The categories of this paper are: nlin
5
The categories of this paper are: gr-qc
3
The categories of this paper are: physics
2
The categories of this paper are: math
17
The categories of this paper are: q-fin
14
The categories of this paper are: math-ph
21
The categories of this paper are: adap-org
27
The categories of this paper are: comp-gas
11
The categories of this paper are: hep-lat
36
The categories of this paper are: cmp-lg
28
The categories of this paper are: alg-geom
8
The categories of this paper are: hep-ex
6
The categories of this paper are: astro-ph