A Decision Support System for Monitoring and Control of Thermal Substations in District Heating Networks


A remote control and monitoring system of thermal request profiles in buildings is crucial for the effective operation of thermal substations connected to a district heating network. The acquired data can be used to develop a dynamic thermal model describing the operation of a thermal substation coupled to a reference building using different surrogate approaches. This work presents a decision support system for predicting the thermal request profile at a building level and optimizing the substation operation. The equipment needed and the development of the remote control monitoring system is initially described. Then, the utilization of surrogate models for generating a dynamic thermal model is presented. Finally, we validate the proposed decision support system through the experimental analysis of an actual unit, serving a building of 6,000m 2 in the district heating network of Kozani, Greece. Surrogate models are generated capable of predicting both the primary and the secondary source temperature. The presented methodology could be utilized in the context of a building model, incorporating the local thermal substation model. Results can be useful towards the optimization of the district heating operation, as well as towards the integration of alternative primary energy sources, potential renewable based ones, which is the case through the on-going decarbonization of the Greek electrical system.

In 2022 7th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM)
Vasilis Balafas
Vasilis Balafas
Software Enginer, PhD Student in Computer Science

My research interests include Machine Learning, Constraint Programming, Optimization, Cloud Computing, and Programmable Matter.