Optimizing Low-Temperature District Heating Networks: A Simulation-Based Approach with Experimental Verification

District heating and cooling systems are becoming increasingly popular due to their potential for exploiting renewable resources and reducing greenhouse gas emissions. In this research study, a novel bottom-up methodology was developed for simulating fifth-generation district heating and cooling systems. The considered methodology is focused on the assessment of the effects of the behaviour of a single building-plant system on the whole water loop. Here, a suitable dynamic simulation model was developed and implemented in a Simscape computer tool. In the model, multiple heat pumps (related to different buildings and interfaced to a unique thermal network) are considered. The developed approach initially focuses on dynamically modelling the operation and adaptation of the modelled heat pumps to follow the building heating demand, through the implementation of suitable control logics for activating and managing each system component. Subsequently, the mutual effects between the network users and the central thermal power station are investigated according to the dynamic thermal energy demand of each single sub-plant. The model takes into account the dynamic behaviour of each component and the occurring effects on the entire network system, by influencing the temperature and flow rate of the considered water loop. Consequently, the efficiency of the network heat pumps as well as the operation of the heat production plant for the network thermal balancing can be assessed. The simulation model was adapted to the configuration of a prototype plant, consisting of 8 heat pumps with a nominal size of 10 kW connected to a low-temperature water loop, thermally balanced by a central heat pump with a size of 95 kW. Several dry coolers are simulated to dissipate the users’ heat production. For validation aims, the obtained results were compared to experimental data gathered from the thermal network prototype. Finally, a bi-level optimization strategy was also proposed to improve the efficiency of the considered low-temperature thermal network system. The first optimization step suggested a water loop temperature control strategy through predictive logics to minimize the consumption of each individual heat pump, whose temperature range was appropriately determined taking into account the operating limits of each user in depending on the heating or cooling requests. The second optimization objective is designed to minimize the energy consumption of the main heat producing unit by adopting specific clustering strategies by taking advantage of the simultaneity of heating and cooling loads. Both optimization procedures showed significant energy savings compared to the reference scenario in which the utilities were decoupled by acting autonomously.