Samanta Alena Weber

This study applies the Physical Optimum (PhO) as a reference value to rate the efficiency
of two technical options for the oxygen supply of a hospital. The systematic comparison of the alternative
processes using the PhO as a benchmark for the minimum input (exergy in this case) required
to run a process with a certain benefit allows to determine the potential for optimization of
each technology. Differences are analyzed by visualizing the losses of each individual production
step in a process as well as by the resulting overall energy demand, including the primary energy.
Possible alternatives are purchasing liquid oxygen from a cryogenic process or the production by
means of Pressure Swing Adsorption (PSA) on site. The cryogenic production shows a lower exergy
demand even though it also has a higher potential for optimization. Yet, the total losses, significantly
impacted by the unavoidable transportation, sum up, resulting in the conclusion that the PSA is the
preferable option overall, considering energy aspects. Finally, additional criteria such as economic,
legal, and structural consequences of the respective choices are briefly outlined.

This paper contains the basic definition and application of the physical optimum as a method for process evaluation and optimization. By means of the exemplary balance of a wood pellet-fired boiler, the conventional efficiency is compared to the PhO. Furthermore, this study demonstrates the possibility of applying the thermodynamic state variable exergy as a physical reference property of a system within the PhO method. To explain the approach, the heat generation in the wood pellet-fired boiler is compared to the supply from a heat pump, which itself is connected to a power plant. Furthermore, the process-independent PhO is explained in order to illustrate the limitations of feasible optimization. Additionally, possible research topics such as the inte-gration of dynamic behavior in the method are approached. As a conclusion, the differences be-tween the methods outline the advantage of the PhO in the optimization process.