A reliable mixed-integer linear programming formulation for data-driven model predictive control in buildings

Integrating renewable energy sources into buildings requires advanced control strategies to enhance demand-side flexibility. Data-driven Model Predictive Control (DMPC) has shown significant promise in this area. Buildings with Thermally Activated Building Structures (TABS) and glass façade present...

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Bibliographic Details
Published in:MethodsX Vol. 15; p. 103470
Main Authors: Klanatsky, Peter, Veynandt, François, Heschl, Christian
Format: Journal Article
Language:English
Published: Netherlands Elsevier B.V 01.12.2025
Elsevier
Subjects:
Building energy management
Data-driven building modelling
Data-driven predictive control
Energy
Model predictive control
Optimization algorithm
Optimization problem formulation with Mixed-Integer Linear Programming for Data-driven Model Predictive Control of buildings with Thermally Activated Building Structures and shading system
Smart shading control
Thermally activated building structure
Smart shading control
Optimization problem formulation with Mixed-Integer Linear Programming for Data-driven Model Predictive Control of buildings with Thermally Activated Building Structures and shading system
Model predictive control
Optimization algorithm
Thermally activated building structure
Building energy management
Data-driven predictive control
Data-driven building modelling
ISSN:2215-0161, 2215-0161
Online Access:Get full text
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Summary:Integrating renewable energy sources into buildings requires advanced control strategies to enhance demand-side flexibility. Data-driven Model Predictive Control (DMPC) has shown significant promise in this area. Buildings with Thermally Activated Building Structures (TABS) and glass façade present flexibility potential, but have a challenging thermal balance, due to high thermal inertia and significant solar gains. In such buildings, a DMPC jointly controlling TABS and the shading system is advantageous. However, the only known implementations enabling this combination rely on a white-box model, limiting the replicability of the approach due to the required modelling effort. To facilitate the implementation of a DMPC for such a combined control task, this paper presents in details a suitable optimisation algorithm:•specifically designed for buildings with TABS and shading systems,•based on a grey-box model of thermal zones (a reduced order state-space model),•using a reliable and efficient Mixed-Integer Linear Programming (MILP) formulation,•handling thermal comfort as constraints, avoiding weighting factors in the objective function. [Display omitted]
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ISSN:2215-0161
2215-0161
DOI:10.1016/j.mex.2025.103470