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Synergistic approach of multi-energy models for a European optimal energy system management tool
(2021)
The investigation of energy transition paths toward a sustainable and decarbonized future under uncertainty is a critical aspect of contemporary energy planning and policy development. There are numerous methods for analysing uncertainties and sensitivities and many studies on sustainable transformation paths, but there is a lack of combined application to relevant use-cases.
In this study, we investigate the sensitivity of energy transition paths to uncertainties in operational and investment costs of power plants in the metropolitan area of Berlin and its rural surroundings.
By employing the linear programming energy system model oemof-B3, we extensively focus on the system's energy technologies, such as wind turbines, photovoltaics, hydro and combustion plants, and energy storages. Greenhouse gas reduction and electrification rates per commodity are realized by selected constraints.
Our research aims to discern how investments in energy production capacities are influenced by uncertainties of other energy technologies' investment and operational costs in the system. We apply a quantitative approach to investigate such interdependencies of cost variations and their impact on long-term energy planning. Thus, the analysis sheds light on the robustness of energy transition paths in the face of these uncertainties.
The region Berlin-Brandenburg serves as a case study and thus reflects on the present space conflicts to meet energy demands in urban and suburban areas and their rural surroundings. An electricity-intensive scenario is selected that assumes a 100 % reduction in greenhouse gas emissions by 2050. With the results of the case study, we show how our approach enables rural and metropolitan decision-makers to collaborate in achieving sustainable energy.
Decision-making in long-term energy planning can be made more robust and flexible by acknowledging the identified sensitivities and enable such regions better to navigate challenges and uncertainties associated with sustainable energy planning.