Digital twin ENERGY 4.0 –
increasing the energy efficiency of industrial plants and systems
- simulation of industrial plants and systems along the entire life cycle - design, operation, maintenance
- increases benefits, reliability, and productivity
- combination of physical and data-driven modelling with artificial intelligence algorithms
- reduces costly sensor technology
- enables remote diagnostics, fault prediction and predictive maintenance
- considers different energy sources (electricity, heat, fuels)
- enables optimal coupling of the sectors (industry, buildings, mobility, energy sector)
- cuts primary energy consumption, costs, emissions, and climate impact
Level of innovation
- combines the energy-intensive industry to Energy 4.0 via AI and offers interfaces to digital B2B market platforms
- implementations in industry at state of the art in research & development
- HM 2020: first broad public presentation of this competence of the TU Wien
Applications & target groups
- retrofit possibility for increasing the efficiency of existing plants and systems
- energy-intensive processes in the manufacturing industry, such as paper and pulp, chemicals and petrochemicals, cement, steel and non-ferrous metals, metal processing, oil and gas, food and beverages
- energy and heat suppliers and their supply networks
Digital Twins for ENERGY 4.0
Digital twins for ENERGY 4.0 – optimal design, operation, and predictive maintenance to increase overall energy efficiency, flexibility, and sustainability