4.7 Article

Automatic modelling of buildings and thermal substations for large district heating systems

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 318, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2021.128351

Keywords

Sustainability; Thermal network; Substation model; Demand prediction; Grey-box model; Demand side management

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This study proposes a method to simulate the thermal behavior of buildings and substations connected to district heating networks, requiring only temperature, mass flow rate, and building volume data for model creation. The model's main strength lies in its applicability to a wide range of district heating systems with only basic data requirements, making it suitable for large networks with thousands of substations. Results indicate that the model can accurately simulate the effects of modifications in district heating system operations with average errors lower than 5%.
Fast prediction of thermal behaviour of buildings and substation connected to district heating systems is an important aspect for implementing technique aimed at reducing primary energy consumption and consequently pollutant emission, such as demand side management, network expansion, renewable sources penetration, integration of waste heat. In this work, an approach to model the end-users connected to a district heating network (each building and each substation) is proposed. A physical model is used, which is calibrated through a proper approach using experimental data. The main strength of the work is that only data that are usually measured in district heating substations (temperature and mass flow rates in the substation) and building volume are required to obtain the model. This makes the model creation and its use automatic and applicable to a wide range of district heating systems also in case other data are not available. This characteristic is essential to make the model suitable for large networks including various thousands of substations. Results show that the model allows simulating the effects of modifications in district heating system operations in terms of building thermal request and temperature variation with an average errors lower than 5% for all the measures analysed.

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