Abstract
Operating district heating systems
with low supply and return temperatures improves heat production and
distribution efficiency, permitting greater integration of renewable
heat sources. Low-temperature district heating is viable without
compromising comfort, but faults in end-users’ heating systems constrain
temperature reductions. Such faults include malfunctioning valves,
improper hydronic balancing, and excessive supply temperature setpoints.
Occupants lack the resources to detect and diagnose these faults, so
there is a need for automated solutions without requiring additional
hardware. This paper proposes a method for improving the operation of an
apartment's hydronic floor heating system using data from room
thermostats, a heat meter and a circulation pump
to identify a grey-box model of the system. The resulting model
virtually senses each room loop's heat flux, flow, return temperature,
and flow coefficient.
The authors tested the model on a low-energy apartment in Denmark,
using it to diagnose causes of high return temperatures, including poor
hydronic balancing and an excessive supply temperature setpoint and pump
setting. The authors also used the model to predict the minimum
permissible supply temperature maintaining comfort, yielding a reduction
in the energy-weighted supply and return temperatures of 8.6 °C and
6.5 °C, respectively.
Original language | English |
---|---|
Article number | 125282 |
Journal | Energy |
Volume | 261 |
Number of pages | 14 |
ISSN | 0360-5442 |
DOIs | |
Publication status | Published - 2022 |
Keywords
- Fault detection and diagnosis
- Virtual sensor
- Grey-box modelling
- Floor heating
- District heating