Beyond GDP Growth: Scenarios for the Swedish energy demand and electricity supply system

Sammanfattning: The project was developed within the “Beyond GDP Growth: Scenarios for sustainable building and planning", a joint program developed by a consortium of Swedish research centers and managed at KTH. The aim of the program is to explore future scenarios that could allow Sweden to achieve both environmental and social goals by 2050. With this goal, ambitious targets were set and four backcasting scenarios that could allow for their fulfilment were defined. In this context, the thesis objective was to focus on the energy sector, that had not been previously studied in detail, and to create a model for the energy demand and for the electricity supply in the four scenarios. To accomplish that, the narratives of the four scenarios were deepened with a specific reference to some parameters affecting the energy model evolution, including the international political and institutional framework and the role of technology in the society. The current Swedish energy demand of electricity, heat and vehicle fuels was used as starting point; then, projections on the evolution of the same throughout the analysed period were made for each scenario, considering the different societal and industrial pathways deriving from the narratives and the energy policies that would be implemented. Additionally, the supply-side model was defined for the electricity system through the adaptation of the Swedish OSeMOSYS model (from OSEMBE model) to the specific scenarios. The obtained technology mix and average LCOEs appear to be significantly different; however, all the systems are fossil free and based on onshore wind, hydropower and waste incineration. In order to validate the results a sensitivity analysis was performed, evaluating the reaction of the four systems to external factors: the presence or not of a minimum imposed hydropower capacity and the increased cost of onshore wind (taking into account the related costs for ensuring the stability of the grid and the matching of demand and supply). For each case, the evolution trend of every scenario was analysed and the optimal technology mix was defined, allowing to identify the most competitive and favourable technologies to be installed.