Model-based monitoring and optimization of geothermal district heating systems

Decarbonization of heating in the built environment in the Netherlands is a critical issues and there is a need to look for alternative fossil-free options to supply such a heat demand. Geothermal energy is one of the potential solution in the Netherlands and for this reason plans were made aiming at growing geothermal energy production from 5 PJ to 200 PJ by 2050. However, in order to fully exploit geothermal as an energy source for district heating, there are several challenges to be addressed by the operators of such systems. Firstly, there is a variable thermal energy demand over the year (seasonality) and operational flexibility of the sources which clashes with the base load supply from geothermal sources. Secondly, geothermal production deals operational challenges such as system inertia limiting the fast response to the demand, flow-chemistry challenges like scaling, corrosion, clogging, and reliability of the components which are reduced under dynamic conditions. To effectively harness this flexibility and minimize operational challenges, a rapid and robust operational decision support system is imperative. By transitioning from a reactive to a proactive approach, organizations can better manage the geothermal energy production while aligning with varying heat demand profiles even in real-time. Ultimately, these efforts aim to not only ensure a sustainable and renewable heating and cooling landscape but also achieve substantial Operational Expenditure (OPEX) savings in the process.