Practical implementation and evaluation of model predictive control for an office building in Brussels
Roel De Coninck,Lieve Helsen +1 more
TLDR
In this paper, a model predictive control (MPC) has been implemented in a medium-sized office building in Brussels, Belgium and the measured performance in comparison with the default, rule-based control (RBC).About:
This article is published in Energy and Buildings.The article was published on 2016-01-01 and is currently open access. It has received 130 citations till now. The article focuses on the topics: Model predictive control & Optimal control.read more
Citations
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Journal ArticleDOI
CasADi: a software framework for nonlinear optimization and optimal control
TL;DR: This article gives an up-to-date and accessible introduction to the CasADi framework, which has undergone numerous design improvements over the last 7 years.
Journal ArticleDOI
Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities
TL;DR: In this paper, the authors introduce a common dictionary and taxonomy that gives a common ground to all the engineering disciplines involved in building design and control, and critically discuss the outcomes of different existing MPC algorithms for building and HVAC system management.
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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Ten questions concerning model predictive control for energy efficient buildings
Michaela Killian,Martin Kozek +1 more
TL;DR: In this article, ten questions concerning model predictive control for energy efficient buildings are posed and answered in detail, and the main benefits of MPC are the explicit consideration of building dynamics, available predictions of future disturbances, constraints, and conflicting optimization goals to provide the optimal control input.
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Whole building energy model for HVAC optimal control: A practical framework based on deep reinforcement learning
TL;DR: In this paper, the authors proposed a real-time control framework based on deep reinforcement learning (DRL) for heating, ventilation and air-conditioning (HVAC) systems.
References
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TL;DR: A comprehensive description of the primal-dual interior-point algorithm with a filter line-search method for nonlinear programming is provided, including the feasibility restoration phase for the filter method, second-order corrections, and inertia correction of the KKT matrix.
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Model predictive control: theory and practice—a survey
TL;DR: The flexible constraint handling capabilities of MPC are shown to be a significant advantage in the context of the overall operating objectives of the process industries and the 1-, 2-, and ∞-norm formulations of the performance objective are discussed.
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Statsmodels: Econometric and Statistical Modeling with Python
Skipper Seabold,Josef Perktold +1 more
TL;DR: The current relationship between statistics and Python and open source more generally is discussed, outlining how the statsmodels package fills a gap in this relationship.
Journal ArticleDOI
Use of model predictive control and weather forecasts for energy efficient building climate control
Frauke Oldewurtel,Alessandra Parisio,Colin N. Jones,Dimitrios Gyalistras,Markus Gwerder,Vanessa J. Stauch,Beat Lehmann,Manfred Morari +7 more
TL;DR: In this paper, the authors investigated how ModelPredictive control and weatherpredictions can increase the energy efficiency in Integrated Room Automation (IRA) while respecting occupant comfort.
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Irradiance Forecasting for the Power Prediction of Grid-Connected Photovoltaic Systems
TL;DR: An approach to predict regional PV power output based on forecasts up to three days ahead provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) and an approach to derive weather specific prediction intervals for irradiance forecasts are presented.