Oskar Vågerö

• Mathisen, Siri Gulaker; Zeyringer, Marianne; Haaskjold, Kristina; Löffler, Konstantin; Mata, Érika & Sandvall, Akram [Vis alle 9 forfattere av denne artikkelen] (2024). The REPowerEU policy’s impact on the Nordic power system. Energy Strategy Reviews. ISSN 2211-467X. 54. doi: 10.1016/j.esr.2024.101454. Fulltekst i vitenarkiv Vis sammendrag

  Energy system models provide us with scenarios for the future energy system, supporting our understanding of the impact of societal changes and adopted policies. To front-load the EU’Fit for 55’ package for 2030 and targets of replacing imported natural gas with renewable electricity, the Nordic countries could contribute by exporting additional electricity to mainland Europe. This paper describes a comparative study including five energy system models – GENeSYS-MOD, ON-TIMES, IFE-TIMES-Norway, highRES, and IntERACT, exploring two decarbonisation scenarios leading up to 2050. The scenarios involved simulating an additional 30 TWh electricity export requirement from 2030. Key findings include Denmark and Norway emerging as major net exporters, with Denmark covering over 60% of the additional export. The models predict that 76%–82% of the new electricity production will come from wind power, split between onshore and offshore installations, highlighting significant investment requirements. These results underscore the Nordic countries’ capacity to support the EU’s renewable energy targets, with wind power being pivotal. This research offers a broad overview over different modelling tools and their behaviour and provides critical insights for policymakers, stressing the need for coordinated Nordic efforts to maximise the benefits of increased electricity exports while ensuring energy system stability and cost-efficiency.

• Vågerö, Oskar; Bråte, Anders; Wittemann, Alexandra; Robinson, Jessica Yarin; Zeyringer, Marianne & Sirotko-Sibirskaya, Natalia (2024). Machine learning of public sentiments towards wind energy in Norway. Wind Energy. ISSN 1095-4244. doi: 10.1002/we.2902. Vis sammendrag

  Across Europe, negative public opinion has and may continue to limit the deployment of renewable energy infrastructure required for the transition to net-zero energy systems. Understanding public sentiment and its spatio-temporal variations is as such important for decision-making and for developing socially accepted energy systems. In this study, we apply a sentiment classification model based on a machine learning framework for natural language processing, NorBERT, on data collected from Twitter between 2006 and 2022 to analyse the case of wind power opposition in Norway. From the 68,828 tweets with geospatial information, we show how discussions about wind power intensified in 2018/2019 together with a trend of more negative tweets up until 2020, both on a regional level and for Norway as a whole. Furthermore, we find weak geographical clustering in our data, indicating that discussions are country wide and not dominated by specific regional events or developments. Twitter data allow for detailed insight into the temporal nature of public sentiments and extending this research to additional case studies of technologies, countries and sources of data (e.g. newspapers, other social media) may prove important to complement traditional survey research and the understanding of public sentiment.

• Vågerö, Oskar & Zeyringer, Marianne (2023). Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models. Energy Research & Social Science. ISSN 2214-6296. 95. doi: 10.1016/j.erss.2022.102913. Fulltekst i vitenarkiv
• Vågerö, Oskar; Kverndokk, Snorre & Nævdal, Eric (2021). Finnes det alternativer til CCS for å redusere utslipp fra sement? . Samfunnsøkonomen. ISSN 1890-5250. s. 31–44.

Se alle arbeider i Cristin

• Vågerö, Oskar (2023). Å vere doktorgradsstipendiat på ITS.
• Vågerö, Oskar (2023). Kva synast folk på Twitter om vindmøller?
• Vågerö, Oskar (2023). Modelling the just allocation of energy infrastructure - Implications of assumptions and definitions of justice on model results.
• Greevenbroek, Koen van; Grochowicz, Aleksander; Zeyringer, Marianne; Noll, Josef & Vågerö, Oskar (2023). Vi treng uavhengig forsking, ikkje drøymetenking om kjernekraft. Aftenposten (morgenutg. : trykt utg.). ISSN 0804-3116.
• van Greevenbroek, Koen; Zeyringer, Marianne; Noll, Josef; Grochowicz, Aleksander & Vågerö, Oskar (2023). Kjernekraft er ikkje naudsynt for Noreg. Det vil heller ikkje lønna seg. Aftenposten (morgenutg. : trykt utg.). ISSN 0804-3116.
• Vågerö, Oskar (2022). Korleis definerast rettferdig fordeling av energi-relatert infrastruktur? Perspektiv frå modellering av energisystem.
• Vågerö, Oskar (2022). Just modelling.
• Vågerö, Oskar (2022). Socially just energy systems and justice principles.
• Vågerö, Oskar (2021). The inclusion of justice perspectives in energy systems modelling - A review of current practices and the way ahead.
• Mathisen, Siri Gulaker; Wolfgang, Ove; Andersen, Simon Brøndum; Andersen, Kristoffer Steen; Belsnes, Michael Martin & Haaskjold, Kristina [Vis alle 16 forfattere av denne artikkelen] (2022). Increased electrification – new generators and consumers. Nordic Energy Outlooks - Final report WP2. SINTEF Energi. ISSN 978-82-594-3791-4. Fulltekst i vitenarkiv

Se alle arbeider i Cristin