K
Krzysztof Arendt
Researcher at University of Southern Denmark
Publications - 28
Citations - 687
Krzysztof Arendt is an academic researcher from University of Southern Denmark. The author has contributed to research in topics: Model predictive control & Energy consumption. The author has an hindex of 10, co-authored 28 publications receiving 352 citations. Previous affiliations of Krzysztof Arendt include Maersk & Gdańsk University of Technology.
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Journal ArticleDOI
All you need to know about model predictive control for buildings
Ján Drgoňa,Ján Drgoňa,Javier Arroyo,Iago Cupeiro Figueroa,David Blum,Krzysztof Arendt,Donghun Kim,Donghun Kim,Enric Perarnau Ollé,Juraj Oravec,Michael Wetter,Draguna Vrabie,Lieve Helsen +12 more
TL;DR: This paper provides a unified framework for model predictive building control technology with focus on the real-world applications and presents the essential components of a practical implementation of MPC such as different control architectures and nuances of communication infrastructures within supervisory control and data acquisition (SCADA) systems.
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ObepME: An online building energy performance monitoring and evaluation tool to reduce energy performance gaps
Muhyiddine Jradi,Krzysztof Arendt,Fisayo Caleb Sangogboye,Claudio Giovanni Mattera,Elena Markoska,Mikkel Baun Kjærgaard,Christian Veje,Bo Nørregaard Jørgensen +7 more
TL;DR: An online building energy performance monitoring and evaluation tool ObepME is proposed, serving as a basis for fault detection and diagnostics and forming a backbone for continuous commissioning, to better characterize, evaluate and bridge energy performance gaps.
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Practical factors of envelope model setup and their effects on the performance of model predictive control for building heating, ventilating, and air conditioning systems
TL;DR: It is found that a difference of up to 20% in cooling cost for the cases studied can occur between the best performing model and the worst performing model, and the primary factors attributing to this were model structure and initial parameter guesses during parameter estimation of the model.
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Performance comparison of occupancy count estimation and prediction with common versus dedicated sensors for building model predictive control
Fisayo Caleb Sangogboye,Krzysztof Arendt,Ashok Singh,Christian Veje,Mikkel Baun Kjærgaard,Bo Nørregaard Jørgensen +5 more
TL;DR: In this article, the authors compared the accuracy and computational demand of two occupancy estimation and prediction approaches suitable for building model predictive control: (1) count prediction based on indoor climate modeling and parameter estimation using common sensors, (2) counting based on data from 3D stereovision camera.
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Numerical analysis by FEM and analytical study of the dynamic thermal behavior of hollow bricks with different cavity concentration
TL;DR: In this paper, the authors investigated the influence of the cavity concentration in hollow bricks on static and dynamic thermal parameters: a time lag, a decrement factor, an equivalent thermal diffusivity (ETD), and equivalent thermal conductivities (ETC).