Energy demand for heating and cooling makes up 73\% of total energy use of buildings [2]. This figure is expected to increase over the coming decades, as demand for cooling energy may rise in the Netherlands due to climate change. The heating and cooling of buildings are at relatively low temperature compared to the industry and thus allowing for a 5th Generation District Heating and Cooling (5GDHC) network with thermal energy storage. Several guidelines are available for the design of 5GDHC substations \cite{ISSO39}, however they do not integrally consider the control design.
Currently, in literature the performance of the substations is generally based on 1-hour measurements yet the control of the short term dynamics have a significant impact on the performance, thus shorter time steps are required to improve the performance.


This study considers the short term dynamics of substations of large utility buildings connected to a 5GDHC grid, allowing for seasonal thermal energy storage and independent bi-directional consumption for all buildings. A hydro- and thermodynamic model including the controllers are compared with a case study of utility buildings at Utrecht University where high frequency operational data is gathered. This provides a view on the causes of the problems and inefficiencies and new insights into improvements on the hydro- and thermodynamics and control of the substation. A new control method for the heat exchanger and for the Heat Pump (HP) group is proposed to maximise the networks capacity.

The use of Model Predictive Control (MPC) controllers is investigated to determine the performance improvements that can be achieved based on a simple physical system model and the energy demand and temperature setpoint predictions. As the short-term dynamics are discussed, the time steps for the MPC optimisation are relatively small while the many on/off switches that are allowed might make it computationally intensive due to large number of binary variables. The flow in some parts might be reversed, which is modelled using binary variables. Finally, as the system is transporting water at different temperatures and different mass flow rates, it is described by bilinear equations. These equations can be linearised by the McCormick relaxations, however they once again increase the computational burden as new binary variables have to be introduced.

The changed proposal for switching conditions could easily be implemented and reduces the temperature limit violations as well as the proposed control method for the warm Heat Exchanger (HEX) as it stabilises the substation control. The proposed method for the temperature setpoint and capacity control showed an improved regulation of the temperature and energy provided by the heat pumps and could even reduce the consumption of conventional heating sources. Finally, the MPC controller shows an increased performance both for the constant and variable flow conditions, but cannot yet be implemented as the computational burden is too large.

District heating systems offer great potential for facilitating the transition towards sustainable heating for metropolitan areas. This research provides an overview of roles and factors relevant to DH systems, identifies stakeholder types, their interests and influence, shows the relationship to system requirements and the lack of stakeholder involvement in the heat planning process. A three-step descriptive system design framework is presented, followed by the identification of improvements for the planning process.

Dutch homes use 70% of their total energy consumption for domestic hot water purposes and space heating. Currently, this energy is yielded through the use of natural gas. In order to meet Dutch Climate Agreement goals, which were agreed upon December 2018, Low Temperature District Heating (LTDH) is expected as being the most promising sustainable heat energy system solution for dense populated districts. To produce sustainable heat, Visser & Smit Hanab (V&SH) have developed a geothermal source which extracts heat from shallow surfaces, between 500 and 1250 meters. Currently, this system is only used to provide heat for greenhouses. Greenhouses are in need of heat supply for more than 5000 hours per year. This thesis presents which other technologies are required to make LTDH with Low Temperature Geothermal Heat (LTGH) as main source a success for heating in district areas. For the case, there are 5 LTDH concepts designed to supply heat to the livings with LTGH. The designed LTDH varies in storage methods, supply temperature in the network, and peak heat supply technologies. The used storage methods are Aquifer Thermal Energy Storage (ATES) and a water tank of 250 liters for each living. The used peak heat supply technologies are decentralized heat pumps, electrical heaters, and a biomass boiler. The following LTDH concepts are designed.1a. Collective peak supply 70 ⁰C2a. Decentral peak supply 70 ⁰C1b. Collective peak supply 50 ⁰C2b. Decentral peak supply 50 ⁰C3. Decentralized heat pumps using 30 ⁰C supply temperatureBased on Key Performance Indicators, these LTDH concepts are compared with each other. Throughout a thermodynamic and economic analysis, it appeard that LTDH concept 3, where decentralized heat pumps are used, scores the best on all the KPIs. concept. That is because the central heat pump, of the other concepts, consumes the most electricity of all the technologies in the system and is always on throughout the entire year. The average efficiency, over a year, of an air heat pump is higher than that of the central heat pump at the LTGH. This is because the air heat pump is switched off when there is no heat demand and with an LTDH, there are losses in the network and the ATES.Future research must be done on the electricity consumption of the central heat pump from the LTGH. If the heat pump can consume less electricity, the load on the electricity during cold hours can be reduced and throughout a year CO2 emissions can be reduced. Also, future research must be done on optimizing the LTDH concepts, so that the savings in CO2 emissions and LCOE will improve. In addition, an NPV analysis should be done to determine how the costs are distributed over the stakeholders.