INNOVATIVE RESEARCH IN SCIENCE
International scientific-online conference
70
DEVELOPMENT OF THE DIGITAL TWIN DATABASE FOR 6 KV
RURAL POWER NETWORKS
A.J.Isakov
F.E.Khojaev
https://doi.org/10.5281/zenodo.14511957
Developing a digital twin for
6 kV rural power networks
represents a
critical step in enhancing energy supply efficiency and improving service quality.
Digital twin technology enables
real-time monitoring
and analysis of the state
of power networks, which is particularly useful for
preventing
failures
,
reducing energy losses
, and
optimizing maintenance processes
.
Additionally, by creating a comprehensive database, it becomes possible to
collect and store valuable operational data about the power networks. Such a
database plays a crucial role in further analysis and informed decision-making,
allowing for better predictions and improvements in network performance.
The creation of a
data repository
serves as the foundational step in
ensuring the effective operation of digital twins. This database aggregates
information about various segments of the power networks, including
parameters such as
voltage levels
,
current resistance
,
current status
, and
other performance metrics. The database also archives historical data, which
enables analysis of changes over time and facilitates accurate forecasting.
Utilizing this information,
digital twin models
can be developed to simulate the
condition of power networks and evaluate different operational scenarios. This
simulation capability contributes significantly to improving overall efficiency
and ensuring
safety
in energy supply.
To develop the digital twin of the research object, the database is organized
into
three main categories
based on the specific characteristics of the system:
1.
Device-Related Data
: This includes information about equipment used
for the distribution and transmission of electricity, such as transformers,
protective elements, overhead and cable lines, and other relevant infrastructure.
Accurate data on the condition, capacity, and operational performance of these
components is essential for modeling and analysis.
2.
Weather Data
: Since external environmental factors like weather
conditions significantly impact energy losses and the performance of power
networks, including weather data is a necessary aspect of developing a reliable
digital
twin.
Factors
such
as
temperature
,
humidity
,
wind
speed
,
and
precipitation
must be considered, as they can affect the efficiency and
stability of power lines.
INNOVATIVE RESEARCH IN SCIENCE
International scientific-online conference
71
3.
Environmental Data
: The location and surrounding environment of
power transmission lines, such as
vegetation
,
terrain
, and
ground conditions
,
play a key role in determining the likelihood of failures and damages. For
example, overgrown trees can cause line faults, and unstable soil can affect the
integrity of poles and structures. Incorporating this data ensures the
development of a
comprehensive
and
robust
digital twin model that accounts
for all external factors.
In conclusion, the development of a
digital twin
for 6 kV rural power
networks significantly improves the efficiency of energy supply systems by
enabling real-time monitoring, failure prevention, and optimized maintenance.
The creation and organization of a well-structured
database
allow for precise
analysis of the system's current state and effective evaluation of various
operational
scenarios.
By
integrating
device-related
,
weather
,
and
environmental
data, the digital twin provides a dynamic and accurate
representation of the power network.
This
technology
enhances
reliability
,
safety
,
and
energy
efficiency
,
contributing to the stability of power supply systems. Ultimately, it serves as a
vital tool for achieving sustainable and optimized rural energy infrastructure,
reducing operational costs, and ensuring uninterrupted electricity supply
.
