Application of digital twin technologies for the optimization of the energy consumption for a wood clattering panels manufacturer
Grishkina, Anastasiia (2023-03)
Grishkina, Anastasiia
03 / 2023
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2023030629987
https://urn.fi/URN:NBN:fi-fe2023030629987
Tiivistelmä
This thesis describes applications of digital twin technology for the optimization of the energy
consumption profile. It is based on the electricity consumption data from a Finnish wood clattering panels manufacturer – Puucomp. The data consists of hourly records for the duration of
36 months. Production simulation was used to identify the bottleneck process with the highest
energy consumption, which is perforation. The Energy Value Stream Mapping (EVSM) method
may be enriched with the digital twin (DT) models and electricity data, enabling energy flow
tracking at the current time.
It has been determined that the highest energy consumption occurs during the morning hours,
with an overall increase in consumption during the cold period. The data has not shown significant dependency on humidity, wind speed, or air pressure. The base load has been considered
with the floor heating and the gap required to fulfill is 60kWh.
Proposed solutions are the utilization of renewable energy sources, technological improvement of
the systems, and production rerouting. The most viable solution is the energy mix, which includes renewable energy sources used with the combination of energy storage systems (ESS) in
the form of batteries. The first scenario consists of the utilization of rooftop space for the solar
panels, which are expected to support floor heating, while ESS is used to support the grid during
peak hours. The second possible scenario includes rooftop leasing, geothermal heat pump utilization for the floor heating, and ESS as a support to the grid.
Utilization of DT technologies has been seen as a viable approach to reduce energy consumption
profile. However, the application of DT is limited by the availability of the data.
consumption profile. It is based on the electricity consumption data from a Finnish wood clattering panels manufacturer – Puucomp. The data consists of hourly records for the duration of
36 months. Production simulation was used to identify the bottleneck process with the highest
energy consumption, which is perforation. The Energy Value Stream Mapping (EVSM) method
may be enriched with the digital twin (DT) models and electricity data, enabling energy flow
tracking at the current time.
It has been determined that the highest energy consumption occurs during the morning hours,
with an overall increase in consumption during the cold period. The data has not shown significant dependency on humidity, wind speed, or air pressure. The base load has been considered
with the floor heating and the gap required to fulfill is 60kWh.
Proposed solutions are the utilization of renewable energy sources, technological improvement of
the systems, and production rerouting. The most viable solution is the energy mix, which includes renewable energy sources used with the combination of energy storage systems (ESS) in
the form of batteries. The first scenario consists of the utilization of rooftop space for the solar
panels, which are expected to support floor heating, while ESS is used to support the grid during
peak hours. The second possible scenario includes rooftop leasing, geothermal heat pump utilization for the floor heating, and ESS as a support to the grid.
Utilization of DT technologies has been seen as a viable approach to reduce energy consumption
profile. However, the application of DT is limited by the availability of the data.