Advancing clean heat with District Heating and Cooling systems
Mengting Jiang defended her PhD thesis at the Department of Mechanical Engineering on February 25.
Heat supply accounts for nearly half of global energy consumption, and it remains heavily dependent on fossil fuels. To achieve global climate targets, the heat sector must shift toward renewable sources鈥攎uch like the electricity sector is already doing. District Heating and Cooling (DHC) networks offer a promising solution, providing an efficient way to integrate renewable and low鈥憈emperature heat sources, particularly in urban areas. Yet in countries where these systems are not widely established, such as the Netherlands, rolling out DHC infrastructure brings a distinct set of challenges. Mengting Jiang addresses these challenges in her PhD research.
started her research by examining the most effective planning and design strategies for developing DHC systems in emerging markets like the Netherlands. She conducted a systematic literature review and highlights key elements in DHC planning, including the development of high-quality heat atlases and accurate forecasting of district energy demand. Jiang identifies bottom-up, data-driven approaches as promising methods for heat demand prediction, particularly those that employ machine learning algorithms. However, data privacy concerns remain a major barrier to obtaining the high-quality data required. Jiang also identifies mature technologies, such as geothermal energy, biomass, and solar energy, as viable heat sources for DHC integration.
DHC network design
For system design, she underscores the importance of including detailed engineering parameters, such as pipe sizing, heat losses, pumping energy, and nonlinear transport models, to ensure accurate and cost鈥慹ffective network design. Special attention is given to 5th鈥慻eneration DHC systems, which offer significant flexibility but require advanced modeling approaches to capture complex interactions between heat sources and end-users.
Reduced-Order Modeling
The second challenge Jiang tackles is the development of high鈥憆esolution yet computationally efficient numerical models capable of simulating the dynamic thermal behavior of DHC networks. These models are essential for enabling advanced control strategies in future low鈥憈emperature, distributed, user鈥慽nteractive systems. To address the trade-off between accuracy and computational cost, she proposes a Reduced鈥慜rder Modeling (ROM) framework for evaluating temperature evolution. Jiang developed and validated the ROM using studies on both single pipe segments and small DH networks, refining the model where necessary.
Application in a real DH system
Finally, she applied the models to a real DH system comprising 22 end-users in the Netherlands. The simulation results demonstrate high prediction accuracy, confirming the practical applicability of the proposed models for system鈥憀evel operation and control. These findings lay the groundwork for future research and support broader implementation of DHC systems in real鈥憌orld settings.
Title of PhD thesis: . Supervisors: Dr. Camilo Rindt, Dr. Michel Speetjens and Prof. David Smeulders.