Analyzing the Effects of COVID-19 Pandemic on the Energy Demand: the
Case of Northern Italy
Abstract
The COVID-19 crisis is profoundly influencing the global economic
framework due to restrictive measures adopted by governments worldwide.
Finding real-time data to correctly quantify this impact is very
significant but not as straightforward. Nevertheless, an analysis of the
power demand profiles provides insight into the overall economic trends.
To accurately assess the change in energy consumption patterns, in this
work we employ a multi-layer feed-forward neural network that calculates
an estimation of the aggregated power demand in the north of Italy,
(i.e, in one of the European areas that were most affected by the
pandemics) in the absence of the COVID-19 emergency. After assessing the
forecasting model reliability, we compare the estimation with the ground
truth data to quantify the variation in power consumption. Moreover, we
correlate this variation with the change in mobility behaviors during
the lockdown period by employing the Google mobility report data. From
this unexpected and unprecedented situation, we obtain some intuition
regarding the power system macro-structure and its relation with the
overall people’s mobility.
Postprint accepted for publication in the proceedings of the 2020
AEIT International Annual Conference (AEIT).
How to cite: P. Scarabaggio, M. La Scala, R. Carli and M.
Dotoli, ”Analyzing the Effects of COVID-19 Pandemic on the Energy
Demand: the Case of Northern Italy,” 2020 AEIT International
Annual Conference (AEIT), 2020. DOI:
https://doi.org/10.23919/AEIT50178.2020.9241136
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