Two-stage stochastic optimization of district energy systems: a case study from Norway

The transition to sustainable district heating and cooling systems represents a critical component in achieving global climate neutrality objectives. This study introduces a two-stage stochastic optimization model designed to optimize the cost-effective expansion of district heating and cooling networks in Norway, with a focus on the growing electrification of thermal energy supply. The model incorporates uncertainties related to electricity price volatility and fluctuations in energy demand. The optimization framework identifies the cost-minimal configuration of renewable energy technologies, including large-scale heat pumps, thermal energy storage systems, and industrial waste heat recovery and many more. A case study conducted in Trondheim, Norway, assesses the techno-economic viability of the various heating, cooling, and energy storage technologies. The findings demonstrate significant potential for cost reduction and emissions mitigation through strategic investments in renewable DHC infrastructure. This study offers a robust decision-support framework for policymakers and urban planners to improve the robustness and sustainability of district energy systems in adaptable climate conditions.