Transparent Regional Energy Modelling for Data-Scarce Arctic Bidding Zones: Diagnostics for Northern Norway

Authors:
Preprint
Publisher website
Google Scholar
Abstract
The energy transition demands planning approaches that reflect local geographic, demographic, and infrastructural constraints, particularly in sparsely populated regions where national-scale models obscure spatially heterogeneous challenges. This study applies a transparent, open-source optimization framework to Northern Norway (NO4), an Arctic bidding zone characterized by dispersed settlements, constrained transmission corridors, and pronounced seasonality in demand and renewable resources. Rather than generating multiple long-term scenarios, the model functions as a diagnostic tool to examine how spatial granularity, high temporal resolution (hourly profiles across four seasons), and data-construction choices shape transition pathways.Results reveal four critical insights. First, regional modeling exposes a substantially stronger growth in electricity demand than national projections suggest, driven by electrification and persistent export dynamics. Second, offshore wind emerges as structurally necessary to meet this demand under realistic hydropower expansion constraints, a finding contingent on capacity factor assumptions requiring sensitivity analysis. Third, temporal mismatch between variable renewable generation and demand materially affects storage needs and trade flows, even in a hydropower-dominated system. Fourth, and most significant, the industrial sector's decarbonization pathway cannot be endogenously determined due to absence of disaggregated regional data; instead, emissions reductions are imposed exogenously, revealing data scarcity, not modeling capability, as the primary bottleneck for regional planning.The study demonstrates that transparent regional models do not merely refine national assessments but expose locally binding constraints, infrastructure trade-offs, and critical data gaps that aggregated models inherently smooth over. For peripheral Arctic regions, such diagnostics are essential to translate climate targets into spatially grounded energy strategies.

This publication has 10 references indexed in Scilit: