**6. Conclusions**

In this work, an extension of CEPA was developed and applied to the energy- and carbon-intensive aluminum industry. Graphical, algebraic and optimization-based approaches for CCEP were applied for the production of specific aluminum products, i.e., aluminum slugs and evaporator panels. Graphical and algebraic approaches determined the minimum amount of zero- and low-carbon energy sources required to achieve the specified emission limit. The transportation model was further applied

to energy planning for two specific products to calculate the optimal electricity mix to reach the specified emission limit with minimum cost.

All the approaches yielded similar results; the first two showed that about 2.14 MWh of zero-carbon or 2.22 MWh of low-carbon, and the same amounts of excess energy (2.14 MWh or 2.22 MWh), are obtained for 1 t of aluminum slugs. The third approach was based on cost optimization and showed that 26% higher electricity cost would be required to achieve the specified CO2 emission target compared to the current case. In principle, this incremental cost can potentially be covered by economic incentives such as an emissions tax. CCEP can thus be used in the future to estimate the amount of such incentives needed to drive industrial fossil-based GHG emissions abatement.

Each approach showed its strengths and weaknesses, as summarized in Table 8. The graphical and algebraic approaches proved to be powerful tools for energy planning of industrial products, since they are intuitive and provide better insights into the problem for both analysis and communication. Optimization-based results are less intuitive; however, optimization automates the procedure and could include more details, including cost optimization. Hybrid approaches are suggested which combine different methods to yield the synergistic advantages of each separate method [63].


**Table 8.** Comparison of the approaches.

This work demonstrated the usefulness of CCEP approaches in the move towards a more sustainable aluminum industry. Since aluminum is widely used in various applications and is highly energy intensive, optimizing the electricity supply mix used in its production could significantly contribute to conserving resources and decreasing the global carbon footprint. However, regarding the optimization of the electricity mix, more detailed exploration regarding the electricity sector should be performed in terms of the cost, emissions, sustainability and availability of low-, zero- and negative-carbon emission sources.

In the future, CCEP analyses will be extended for targeting GHG (CO2 Equation emissions) and other footprints. Various options for carbon capture could be incorporated, including technologies to achieve GHG emissions reductions. Additionally, CO2 emissions reductions could be analyzed by including mass integration to minimize emissions and the use of materials. Analyses could also be expanded to more aluminum products and to include more details regarding types of energy sources

(renewable energy could be separated to hydro, photovoltaics, geothermal, wind, biomass, etc.), and their availability and pricing (e.g., hourly based), including future prices. Multiscale application of PI techniques could be used to improve material and energy efficiency to reduce energy consumption and emissions at the process, TS and supply chain network levels [33]. The methodology will be extended to account for variations in the ratio of primary and secondary aluminum within a circular economy framework and to account for negative emission technologies, and will include the combined use of all three proposed approaches.

**Author Contributions:** R.G., L.C. and Z.K.: conceptualization and methodology; R.G.: data curation, formal analysis, ˇ and original draft preparation; L.C.: resources and supervision; L. ˇ C., M.H., R.R.T. and Z.K.: writing-review and ˇ editing. All authors have read and agreed to the published version of the manuscript.

**Funding:** The authors are grateful for funding support from the companies Talum d.d. and Talum Inštitut d.o.o. and from the Slovenian Research Agency (research core funding No. P2-0412 and P2-0032 and projects N2-0138 and J7-1816).

**Conflicts of Interest:** The authors declare no conflict of interest.
