Decentralized Thermal Energy Storage for District Cooling: A techno-economic case study on the feasibility of small scale latent thermal energy storage in Gothenburg - Häggström, Felicia; Wessén, Isa (My University, 2026)
District cooling (DC) networks are expanding. To accommodate future network ex pansion and mitigate increasing peak demand, thermal energy storage (TES) can be incorporated into the DC networks. Decentralized storage has the potential to re lieve production and network capacity during peak demand hours by storing cooling energy at individual customer sites. This thesis investigates the theoretical potential of decentralized TES containing phase change materials, called latent thermal energy storage (LTES), both from the perspective of the customer and producer. The anal ysis uses mixed integer linear programming (MILP) together with operational data from a critical section of Gothenburg’s DC network (2025). The results indicated that peak demand in the Almedal area could be reduced by 6.1% using measured data, and by 10.0% with optimized operating conditions. Network flow reductions were also evaluated, showing a decrease of around 3.2% using measured data, cre ating potential for new customers to connect to the network. Optimizing operating conditions alone reduced the flow by 34.9%, while the addition of storage provided a reduction by 10.0%. The economic analysis showed that profitability is highly case-dependent and primarily driven by achieved peak reduction. While customers generally benefit more economically from LTES implementation than producers, a cost-sharing approach improved the profitability for both parties if sufficient peak reduction is achieved. With the calculated investment cost of 2149 SEK/kWh, the producer would be willing to cover between 45-81% of the investment to remain profitable, depending on discount rate. In contrast, the customer could, indepen dently of discount rate, pay for the full storage and still remain profitable over a 10 year project period.
Keywords: PCM; district cooling; latent thermal energy storage; cooling storage; Gothenburg; energy system modeling; linear programming; mixed-integer linear programming; storage optimization; peak reduction; HVAC