Location, location, location: optimal placement of new electricity production in the nordic energy system amidst large-scale electrification - Bertilsson, Joel; Göransson, Lisa; Johnsson, Filip (Renewable energy focus, 2026)
•High-resolution model optimizes the siting of renewable energy in the Nordic region.•Detailed representation of the grid and local production conditions for renewables.•Proximity to demand and full-load hours are key factors in optimal siting.•Grid capacity assumptions have strong impacts on model output. Renewable electricity generation is expected to play a pivotal role in the global shift toward electrification. However, the inherent variability of renewable energy sources, in addition to factors such as local weather patterns and grid limitations, poses a significant challenge in terms of determining the optimal size and placement of distributed generation units. This study tackles this issue by applying a novel, high-resolution energy systems model that is tailored to the Nordic region. The model is designed to capture with high accuracy local nuances in relation to grid infrastructure, weather patterns, and demand profiles. The model minimizes the total system costs, accounting for both investment and operational expenditures, through the optimal integration of variable renewable energy sources and dispatchable generation units. The findings indicate that the siting of renewable generation is primarily influenced by a combination of a high number of full-load hours and proximity to the electricity demand, with the latter becoming increasingly important under high-demand conditions. Among renewable technologies, solar photovoltaic systems exhibit the strongest correlation with demand center proximity, whereas offshore wind is mainly constrained by a high potential annual production capacity. In addition, assumptions regarding the availability of electricity grid capacity are shown to have a significant impact on the results, with up to 26% of production being relocated when 100 % thermal grid capacity is available, as compared to when 30% of grid capacity is reserved for contingency events.