- Increasing complexity of (industrial) energy systems and energy procurement due to volatile markets
- Increased requirements to achieve sustainable and cost-efficient production
- Interdisciplinary knowledge necessary to achieve energy & cost efficiency
- Increasing amount of data to handle due to rise of IoT devices
- Limited information and ressources in energy teams lead to sub-optimal systems & operation strategies
- Structure, dimension and operation of energy systems need to be optimized for cost efficiency
- Energy markets, production and weather forecast integrations lead to unprecedented cost advantages
- Efficient tools are needed to support energy team on the complex and interdisciplinary optimization tasks
- Artificial intelligence is able to handle huge amount of data and to identify optimization measures
- Digital twins can be used to generate synthetic data in simulations for different environment scenarios
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