Journal Article10.1080/19401493.2011.648343
A model predictive control optimization environment for real-time commercial building application
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TL;DR: In this paper, a model predictive control (MPC) environment is described, which integrates Matlab and EnergyPlus with a modified particle swarm optimizer to predict optimal building control strategies, allowing real-time optimization considering operator overrides and updated weather forecasts.
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Abstract: A model predictive control (MPC) environment is described. The environment integrates Matlab and EnergyPlus with a modified particle swarm optimizer to predict optimal building control strategies. A supporting framework is described which couples the environment to a building automation system, allowing real-time optimization considering operator overrides and updated weather forecasts. Challenges unique to integration with EnergyPlus for real-time optimization are discussed. Application of the environment is demonstrated in two simulation cases. First, the environment is used to determine hourly cooling set points minimizing daily energy cost for EnergyPlus's Benchmark Large Office building. Results suggest 5% cost savings during the study period. Second, the environment is used to determine hourly supply water temperature and circulator availability that minimize daily energy consumption for a small office building having a thermally activated building system (TABS). Compared to the base case, energy sa...
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Citations
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.
623
Review of building energy modeling for control and operation
Xiwang Li,Jin Wen +1 more
TL;DR: In this paper, an up-to-date overview of research on application of building energy modeling methods in optimal control for single building and multiple buildings is also summarized in this paper, and different model-based and model-free optimization methods for building energy system operation are reviewed and compared.
584
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.
Assessing gaps and needs for integrating building performance optimization tools in net zero energy buildings design
TL;DR: The findings indicate a breakthrough in using evolutionary algorithms in solving highly constrained envelope, HVAC and renewable optimization problems and some future directions anticipated or needed for improvement of current tools are presented.
439
Electricity load forecasting by an improved forecast engine for building level consumers
TL;DR: A new prediction model for small scale load prediction i.e., buildings or sites is outlined, based on improved version of empirical mode decomposition (EMD) which is called sliding window EMD (SWEMD), a new feature selection algorithm and hybrid forecast engine.
386
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