(82a) Offline Optimisation of District Heating Networks (DHN) Using Grey Box Models

According to the International Energy Agency (IEA) 2023 report, improving energy efficiency is a significant strategy for reducing global energy waste and carbon emissions. This research focuses on enhancing the efficiency of a district heating network (DHN), a critical component of the global thermal energy generation sector, through optimisation. The DHN generates thermal energy and distributes it to consumers according to their dynamically changing power demands, influenced by varying meteorological conditions.

Since these power demands and weather conditions are both unpredictable and dynamic, dynamic real-time optimisation (DRTO) is necessary for effective network optimisation. However, DRTO requires computationally inexpensive models to perform repeated dynamic optimisations (DO) in real time. To address this, this research develops a fast grey box model designed for integration into a DO algorithm.

In this paper, only dynamic (offline) optimisation of the DHN will be performed, demonstrating the feasibility of implementing a DO with the developed grey box model. This serves as a foundational step toward enabling DRTO in future research.