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@ARTICLE{Mork:1020537,
author = {Mork, Maximilian and Redder, Florian and Xhonneux, André
and Müller, Dirk},
title = {{R}eal-world implementation and evaluation of a {M}odel
{P}redictive {C}ontrol framework in an office space},
journal = {Journal of building engineering},
volume = {78},
issn = {2352-7102},
address = {Amsterdam [u.a.]},
publisher = {Elsevier},
reportid = {FZJ-2024-00250},
pages = {107619 -},
year = {2023},
abstract = {In this work, Model Predictive Control (MPC) is
experimentally implemented on a Heating, Ventilation and Air
Conditioning (HVAC) system of a large-scale office space. As
controller model, a physics-based Modelica building model is
calibrated based on historic data pursuing an iterative,
nonlinear optimization approach. For the calibration period
with a horizon of seven weeks, the calibrated model exhibits
a high model accuracy with a Root Mean Square Error (RMSE)
of 0.49 between the measured and estimated room temperature.
The MPC toolchain includes modules for state estimation and
forecasts of disturbances quantities (such as outdoor
temperature, solar radiation including calculation of the
direct and diffuse fraction, supply temperatures and
occupancy). The MPC execution comprises the operation of
heating based on radiators and floor heating (via regulation
of valve openings) as well as shading of three Venetian
blind systems (via regulation of vertical position and slat
inclination angle). The experiment is conducted during a
heating period with a duration of three weeks from October
21 to November 11, 2022. The heating actuators are
controlled considering their typical dynamics and take into
account the night setback during unoccupied office periods.
User acceptance of the automated shading control is included
through additional cost function terms for the shading
operation. The field test reveals the predictive control
capabilities of the proposed MPC toolchain in a real-life
scenario, demonstrating energy-efficient building operation
and total average discomfort of 0.53 Kh/d. The MPC
formulation provides flexibility regarding adjustability of
the control towards energy efficiency, thermal comfort,
daylight transmission and non-oscillating shading control.
Finally, the disturbance forecast accuracies for outdoor
temperature and the solar radiation quantities are evaluated
and the MPC control performance is compared against a
conventional control approach.},
cin = {IEK-10},
cid = {I:(DE-Juel1)IEK-10-20170217},
pnm = {1121 - Digitalization and Systems Technology for
Flexibility Solutions (POF4-112) / 1123 - Smart Areas and
Research Platforms (POF4-112) / EG2050: LLEC-Verwaltungsbau:
Klimaneutraler Verwaltungsbau als aktiver Teil des Living
Lab Energy Campus (LLEC) (03EGB0010A) / Forschungs- und
Demonstrations-Projekt 'LLEC::JuPilot' (03EK3047) / LLEC -
Living Lab Energy Campus (LLEC-2018-2023)},
pid = {G:(DE-HGF)POF4-1121 / G:(DE-HGF)POF4-1123 /
G:(BMWi)03EGB0010A / G:(BMBF)03EK3047 /
G:(DE-HGF)LLEC-2018-2023},
typ = {PUB:(DE-HGF)16},
UT = {WOS:001138132300001},
doi = {10.1016/j.jobe.2023.107619},
url = {https://juser.fz-juelich.de/record/1020537},
}