Strategic capacity expansion planning in hydro-dominated power systems: Insights from the NordicsShow others and affiliations
2026 (English)In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 344, article id 139771Article in journal (Refereed) Published
Abstract [en]
Conventional capacity expansion planning (CEP) relies on a perfect-foresight planning horizon and linear investment optimisation, which fail to capture the non-linear dynamics of electricity markets. In the Nordics, hydro-related weather variability plays a critical role in maintaining the robustness of the power system. This paper addresses the intra-year perfect-foresight limitation in current CEP models, focusing on hydro-dominated power systems with substantial hydro reservoir capacity, using Sweden's decarbonisation pathway toward 2050 as a case study. Our approach provides a robust long-term CEP framework by leveraging short-term price forecasts to guide storage dispatch decisions. The proposed CEP model has been historically validated and captures the dynamics of seasonal storage hydro reservoirs, achieving deviations of less than €1/MWh in annual average prices across all Swedish bidding zones. A comparative analysis between the proposed and conventional CEP models (cGrid and GenX), together with the Ten-Year Network Development Plan (TYNDP 2024), reveals a broad alignment in capacity expansion and dispatch under an average weather year. However, in a problematic weather year, with correlated low wind output and reduced hydro inflows, significant divergences emerge, with half-year price averages differing by up to ±€40/MWh. These discrepancies are mainly driven by contrasting approaches to hydro reservoir modelling. Notably, the proposed CEP model recommends a 37.5 % increase in firm nuclear capacity to mitigate supply shortages, whereas the conventional CEP suggests a 4.4 % reduction, thereby increasing reliance on weather-dependent resources. These findings underscore the limitations of perfect-foresight CEP in power systems with substantial seasonal storage resources.
Place, publisher, year, edition, pages
Elsevier BV , 2026. Vol. 344, article id 139771
Keywords [en]
Extreme weather years, Long-term power system planning, Multiple weather years, Perfect-foresight, Power market modelling, Seasonal storage
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering Energy Systems
Identifiers
URN: urn:nbn:se:kth:diva-375469DOI: 10.1016/j.energy.2025.139771Scopus ID: 2-s2.0-105025784544OAI: oai:DiVA.org:kth-375469DiVA, id: diva2:2028965
Note
QC 20260116
2026-01-162026-01-162026-01-16Bibliographically approved