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Mathematical optimization methods are used to generate the cost optimal solution for this problem.
In a carbon optimal solution, the share of ECF is 39% of the life cycle carbon footprint, whereas in a cost optimal solution, the share of ECF is 28% of the life cycle carbon footprint.
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This study presents different cost optimal solutions of building and technical systems for nZEBs in Italy.
It critically analyses how such strategies contribute to developing timely low cost optimal solutions for the steel industry.
Without proper financial subsides, net ZEB solutions are still far for being economic feasible, having a global cost 212 313 €/m2 higher than cost optimal solutions.
Especially for large engineering systems it is not possible to identify cost optimal solutions if the various types of functional and statistical dependencies in the systems are not explicitly addressed.
Literature illustrates the difficulties in obtaining the lowest-cost optimal solution to an ore blending problem for blast furnaces by using the traditional trial-and-error method in iron and steel enterprises.
The global cost is investigated too, as further criterion, in order to detect the cost-optimal solution.
Compared to the cost-optimal solution, other objectives might lead to reduced primary energy consumption for 7.21% or lower emission for 91.85% with 43.35% and 83.1% larger costs.
It is well recognized that in the long run, the implementation of energy efficiency measures is a more cost-optimal solution in contrast to taking no action.
Then, following the adoption of these packages, the global cost over the lifecycle of the building is calculated, in order to identify the cost-optimal solution.
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