How to Explore and Analyze the Decision Space in the Synthesis of Energy Supply Systems

A method is presented to systematically analyze the decision space in the synthesis of energy supply systems. Commonly, synthesis problems are solved by mathematical optimization yielding a single optimal design. However, a single solution does not provide sufficient decision support for the designer: Optimization is based on a model which never perfectly represents reality. Thus, the designer will be forced to revise parts of the optimal solution. We aim to support the design process by automatically identifying important features of good solutions. For this purpose, we analyze near-optimal solutions. To rigorously explore the full decision space, we minimize and maximize both the number and the capacity of units while keeping the cost within a specified range. From this analysis, we derive insight into the correlations between decisions by evaluating correlation coefficients between the near-optimal designs. To support the decision maker, we represent the range of good design decisions and their correlations in the flowsheet of the energy supply system. The method is illustrated for the design of an energy supply system in the pharmaceutical industry.

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