Demand response of district heating using model predictive control to prevent the draught risk of cold window in an office building

Yuxin Wu*, Aleksi Mäki, Juha Jokisalo, Risto Kosonen*, Simo Kilpeläinen, Sonja Salo, Hong Liu, Baizhan Li

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

13 Citations (Scopus)

Abstract

Demand response of district heating provides one tool for decreasing cost and emissions in the whole energy system. However, when seeking cost savings and emission reductions, it is also important to consider thermal comfort. Thus, the overall and local thermal comfort of occupants were investigated during the experimental study while applying the demand response of space heating. Thermal manikin measurements were used to reveal the draught risk of convection flow caused by cold windows. Results show that when the surface temperature of windows was below 15°C while the thermostat valves of the radiators were closed, the draught risk became unacceptable. The main objective of the simulation with the developed predictive control algorithm (MPC) was to show how much the minimization of draught risk by limiting minimum window surface temperature to 15°C during decentralized demand response control effects heating energy cost-saving potential. Results show the maximum annual district heat energy cost saving by demand response control without minimization of draught risk is 4.8% and 3.8% with energy-efficient (U=1.0 W/m2K) or poor (U = 2.6 W/m2K) windows respectively, but the draught risk is high with the poor windows. The minimization of draught risk has an insignificant effect on the cost-saving with the energy-efficient windows, but the cost-saving was reduced to 2.3% and draught risk significantly decreased with the poor windows. Thus, it is necessary to use the window temperature restriction with demand response control of radiator heating to prevent the draught risk of cold poorly insulated windows within the thermal comfort range.
Original languageEnglish
Article number101855
Number of pages14
JournalJournal of Building Engineering
Volume33
Early online date28 Sep 2020
DOIs
Publication statusPublished - Jan 2021
MoE publication typeA1 Journal article-refereed

Keywords

  • demand response
  • thermal comfort
  • model predictive control
  • thermal manikin
  • optimization

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