In the past decade, several control strategies have been studied and applied to building energy management systems with the goal of increased cost reduction and energy efficiency. This paper proposes two different control strategies for a Heating, Ventilation and Air-Conditioning (HVAC) system installed in a three-zone office building. Firstly, this study introduces the online parameter estimation method to identify the parameters of the original system. In addition, the adaptive version of the Model-based Predictive Controller (MPC), which uses the previously estimated parameters, is connected to the system in order to regulate the inner temperatures of the three zones. The scope of the parameter estimator and model predictive controller's combination is to adjust the indoor temperatures to the reference values while achieving optimal operational costs and constant thermal comfort. Secondly, a PI controller tuned by weather conditions is briefly presented, and a comparative study is carried out between the two strategies' results. The main scope is to bear comparison between the classic and the optimal, more complex control strategies.
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Control strategies for HVAC systems
Semantic Scholar · Engineering · 2019
Abstract
In the past decade, several control strategies have been studied and applied to building energy management systems with the goal of increased cost reduction and energy efficiency. This paper proposes two different control strategies for a Heating, Ventilation and Air-Conditioning (HVAC) system installed in a three-zone office building. Firstly, this study introduces the online parameter estimation method to identify the parameters of the original system. In addition, the adaptive version of the Model-based Predictive Controller (MPC), which uses the previously estimated parameters, is connected to the system in order to regulate the inner temperatures of the three zones. The scope of the parameter estimator and model predictive controller's combination is to adjust the indoor temperatures to the reference values while achieving optimal operational costs and constant thermal comfort. Secondly, a PI controller tuned by weather conditions is briefly presented, and a comparative study is carried out between the two strategies' results. The main scope is to bear comparison between the classic and the optimal, more complex control strategies.