Modeling urban energy transitions under uncertainty: Integrating robust and adaptive planning with economic and financial considerations

Growing demand, technological change, weather variability, and evolving policy frameworks pose significant uncertainties for long-term urban energy planning. This study develops and applies an integrated TIMES_NE urban energy modeling framework to examine adaptive planning pathways for Gothenburg, Sweden, over the 2018–2050 planning horizon. The framework combines scenario analysis, system-cost optimization, price sensitivity analysis, and stakeholder-informed uncertainty processing to evaluate interactions among buildings, district heating, transport, electricity, and biomass resources. A central novelty of the study is the explicit representation of cross-sectoral resource competition, particularly the competition for limited biomass resources between district heating and transport biofuels. The results show that building rehabilitation under the City Energy Plan scenario reduces annual district heating demand for existing multi-family housing by 16% by 2050. Transport energy consumption decreases by 57% under the City Energy Plan scenario, compared with 42% in the Reference scenario, mainly due to modal shift, efficiency improvements, and vehicle electrification. Across scenarios, total electricity demand increases by 43–56% above 2018 levels by 2050, with heat pumps accounting for 14.5–19% and electric vehicles for 24–25% of total electricity use. Bio-resource consumption increases from 0.9 TWh in 2018 to as much as 4.8 TWh by 2050 under base bio-resource pricing, creating significant competition between heating and transport. The district heating system shifts toward biomass combined heat and power under low bio-resource costs, but toward central heat pumps under high bio-resource costs. These findings demonstrate that adaptive, cross-sectoral planning is essential for avoiding resource lock-in, managing electrification-driven grid pressure, and aligning short-term municipal energy targets with long-term resilient urban decarbonization pathways.