Energy efficiency is a hot topic, because reducing consumption reduces cost and pollution at the same time. When not only one plant, but a system of plants as found in a whole industrial park is considered, savings potential is increased enormously, but so also is the complexity.

Energy consumption of every single plant is not static but depends on factors as environmental temperature, product demand, and energy cost structure, but is also influenced by 'soft' factors as preference decisions done by humans. On the larger scale (the picture on the right shows the chemical park Knapsack near Cologne), the multitude of demands has to be served and ideally, implemented solutions shall cope well with changing demands (new plants, production change leading to energy flow structure changes). We employ evolutionary algorithms at different levels of this highly complex optimization problem.

This project was funded by BMWi and coordinated by the Chair of Technical Thermodynamics at the RWTH Aachen.