Implementing a highly adaptable method for the multi-objective optimisation of energy systems

In order to mitigate climate change, the energy sector undergoes a transformation towards climate-neutral future based on renewable sources. Energy system models generate insights and support decision making for this transformation. face of, e.g., growingly complex important environmental assessments stakeholder structures, considering multiple objectives in these becomes essential realistically reflect existing interests. However, there is lack of highly adaptable incorporating objectives. We present an implementation augmented epsilon-constraint method with optimisation framework Backbone. It enables simultaneous objectives, such as minimisation costs, CO2 emissions or self-sufficiency broad range systems including different sectors scales. For purpose, new objective functions constraints are implemented They used by external algorithm sequence parallelised optimisations cope complexity real-world applications. The further scalable large systems. Applications Western Southern European power 2050 sector-coupled mixed-integer household-level model demonstrate its benefits adaptability. Pareto fronts, technology use trade-offs analysed quantified. sector, emission reductions up 90% can be achieved at marginal abatement costs below 100 EUR/(tCO2). household, imports from public grids reduced 70% 20% higher cost average 2.6ct/kWh. expect that presented methods reveal valuable modellers makers.