  The challenges of power quality are an emerging topic for the past couple of
years due to massive changes occurring in low voltage distribution networks,
being even more emphasized in the years marked by the novel COVID-19 disease
affecting people's behaviour and energy crisis increasing the awareness and
need of end-users energy independence. Both of these phenomena additionally
stress the need for changes in distribution networks as the traditional
consumption patterns of the end-users are significantly different. To overcome
these challenges it is necessary to develop tools and methods that will help
Distribution System Operators (DSOs). In this paper, we present a geographic
information system (GIS)-based tool that, by using open source technologies,
identifies and removes errors both in the GIS data, representing a distribution
network, and in the consumption data collected from the smart meters. After
processing the initial data, a mathematical model of the network is created,
and the impact of different electricity consumption scenarios on power quality
(PQ) indicators voltage magnitude, voltage unbalance factor, and total voltage
harmonic distortion are calculated. The results of simulations are visualised
using a GIS tool, and based on the results, time periods that are most affected
by the change of end-users behaviour are detected. The potential of the
end-users in the PQ improvement is investigated and an algorithm that shifts
consumption to more adequate time periods is implemented. The results show that
the pandemic negatively affect all analysed PQ indicators since the change in
the average value of PQ disturbances increased both during the hard and
post-lockdown period. The time-shifting of consumption shows significant
potential in how the end-users can not only reduce their own energy costs but
create power quality benefits by reducing all relevant indicators.
