TY - JOUR
T1 - Hydraulic parameter estimation for district heating based on laboratory experiments
AU - Agner, Felix
AU - Jensen, Christian Møller
AU - Rantzer, Anders
AU - Kallesøe, Carsten Skovmose
AU - Wisniewski, Rafal
PY - 2024/12/15
Y1 - 2024/12/15
N2 - In this paper we consider calibration of hydraulic models for district heating networks based on operational data. We extend previous theoretical work on the topic to handle real-world complications, namely unknown valve characteristics and hysteresis. We generate two datasets in the Smart Water Infrastructure Laboratory in Aalborg, Denmark, on which we evaluate the proposed procedure. In the first data set the system is controlled in such a way to excite all operational modes in terms of combinations of valve set-points. Here the best performing model predicted volume flow rates within roughly 5 and 10 % deviation from the mean volume flow rate for the consumer with the highest and lowest mean volume flow rates respectively. This performance was met in the majority of the operational region. In the second data set, the system was controlled in order to mimic real load curves. The model trained on this data set performed similarly well when evaluated on data in the operational range represented in the training data. However, the model performance deteriorated when evaluated on data which was not represented in the training data.
AB - In this paper we consider calibration of hydraulic models for district heating networks based on operational data. We extend previous theoretical work on the topic to handle real-world complications, namely unknown valve characteristics and hysteresis. We generate two datasets in the Smart Water Infrastructure Laboratory in Aalborg, Denmark, on which we evaluate the proposed procedure. In the first data set the system is controlled in such a way to excite all operational modes in terms of combinations of valve set-points. Here the best performing model predicted volume flow rates within roughly 5 and 10 % deviation from the mean volume flow rate for the consumer with the highest and lowest mean volume flow rates respectively. This performance was met in the majority of the operational region. In the second data set, the system was controlled in order to mimic real load curves. The model trained on this data set performed similarly well when evaluated on data in the operational range represented in the training data. However, the model performance deteriorated when evaluated on data which was not represented in the training data.
KW - District heating
KW - Experiment
KW - Hydraulic
KW - Model
KW - Parameter estimation
UR - http://www.scopus.com/inward/record.url?scp=85206983561&partnerID=8YFLogxK
U2 - 10.1016/j.energy.2024.133462
DO - 10.1016/j.energy.2024.133462
M3 - Journal article
SN - 0360-5442
VL - 312
JO - Energy
JF - Energy
M1 - 133462
ER -