Application of digital twin technologies for the optimization of the energy consumption for a wood clattering panels manufacturer

Abstract

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.