In the next ten years, the Baltic countries ― Estonia, Latvia, and Lithuania ― are planning large investments in renewable power generation and transfer capacity, substantial phase-out of fossil-based power generation, and desynchronization from the Russian electricity grid. In this article, the operational impacts of these changes on the Baltic energy system from 2017 to 2030 are studied with an open-source Backbone energy system model. The operation of Estonian, Latvian and Lithuanian power and heat, transport, and building sectors are optimized simultaneously on an hourly level, and results are analysed with operational, environmental, economic, and security indicators.
Results suggest that the planned transition would support Baltic targets in renewable generation (from 45% to 92%) and self-reliance (2.3 TWh increase in domestic power generation and 5.5 TWh decrease in natural gas imports) with a moderate impact on system costs. However, an increase in transport CO2 emissions could risk national non-ETS targets. The hourly operation of the system, with a high share of wind and solar, is based on active use of storages and interconnectors. Model results raise concerns about the amount of Estonian dispatchable capacity, the commercial feasibility of Latvian natural gas CHP’s, and the high ramping rates of Lithuanian interconnectors.
In the European Green Deal, EU Commission has set a goal to reduce greenhouse gas emissions in the transport sector by 90% by 2050 compared to the 1990 level. Most likely, transport decarbonization will rely on a rapid expansion of electric and hydrogen vehicle fleet, which would seriously affect not just overall electricity demand, but also the shape of the electricity consumption curve. Consequently, our research focuses on integrated energy and transport modelling when analyzing its development pathways up to 2050 and beyond. This paper describes how already established transport modeling practices can be further improved by differentiating vehicles by age groups and setting vehicle age distributions to improve the representation of vehicle stock, fuel efficiencies and emissions, especially for countries that have non-declining vehicle age distributions. Modeling results using proposed and traditional approaches were compared for the Lithuanian case. It shows that the transport fuel shift using the proposed approach is more gradual than the traditional one. Diesel cars are phased out by 2050 versus 2040. Furthermore, the proposed approach provided more realistic CO2 emissions, 7% lower emissions for 2018 than estimated based on statistical data, while traditional approach was 27% lower.
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