Optimization modeling of the district cooling system in Gothenburg

Abstract

Göteborg Energi is the sole provider of district cooling in Gothenburg. The district cooling system (DCS) is currently expanding with an increase in the installed capacity of the chillers. The installed capacity of chillers in 2030 will be double the current capacity. Besides, a thermal energy storage (TES) in the form of a tank that stores cold water will be installed in the system in 2024. Therefore, to determine the optimal operation of the DCS in the future, the impact of future investments on the operation of the system must be investigated. To evaluate the effect of the different investments and the interaction of the cooling system with the heating and electricity sectors, an optimization study through the software GAMS has been conducted in this thesis. The model has been formulated as a mixed-integer optimization problem. Models and cases were created to examine different situations. The main goal of the models was to determine the optimal functioning of the DCS. Three different cases were set up to analyze different scenarios. The first case compared the optimal operation of the district cooling system to a hypothetical best alternative case of having individual chillers in buildings. The impact of the thermal energy storage on the system was investigated in the second case. In the third case, different scenarios were considered to evaluate the impact of the developments in the heating and electricity systems on the operation of DCS in 2030. It was found that the district cooling system was more economical and environmentally friendly than the hypothetical best-case alternative of a conventional cooling system. The results also showed that the installation of the TES in the system helps achieve significant savings in chiller running costs. The major result from the third case was that the future investments in the district cooling system depend largely on the developments in the electricity system. The main uncertainty in these results was due to the exclusion of the network-based constraints and pumping costs. These can have a significant impact on the results. Hence, the network must be included in the models. By including the network, the chilled water generation and distribution can be optimized together. For this purpose, the different methods to model the network effectively in a numerical model were investigated. The two methods considered in this case are the ‘Fixed pumping parameter’ method and the ‘Linked cost functions’ method. Further, using the best method from the above, the impact of the tank was evaluated and how it changes when modeled with the network was determined. It was concluded that the linked cost functions method has more detailed representation of the network and is a more effective method to model the network. Lastly, it was seen that the optimal operation of the TES depended on the control strategy of the TES and the location of the chillers. The dispatch of the chillers is much changed when the network is included in the model. Hence, the inclusion of the network is necessary for creating realistic models.