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Abstract
Predicting the outcome of possible changes in interlinked industrial energy systems is hard, especially in retrofit scenarios. This leads to severe uncertainties when making investment decisions. In this paper, a new combined optimization approach is presented that aims to support decision-making in these cases. Our approach links models for the optimal design of supply systems and heat recovery systems with operational constraints and is specifically designed for retrofit applications. It is formulated as a single combined mixed-integer linear programming (MILP) problem. The approach is applied in a case study representing a typical industrial process, where the supply system and the heat recovery are adapted. The optimal solution shows a cost-effective way for a transition to more efficient use of energy and an increased share of renewable sources.
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