Abstract
The purpose of the study is to design a method analyzing dynamic behavior of cooling coil in order to be applicable in online simulations. Coils account for the highest energy consumers among other components in an Air Handling Unit (AHU). Essential data as input-output of neural network is provided using energy and mass conservation equations. An implicit numerical method is used to solve dynamic equations of coil. The results of mathematical methods are applied in the output of neural network to design an online model. The proposed model is based on an active coil used in Heating, Ventilation and Air Conditioning (HVAC) systems of clean rooms in Iran Pasteur Institute. Since in active air handlers, input and outputs are not measured, here we model air conditioning systems generally. The results in comparison with actual system data indicate an acceptable performance of the proposed method, so that combination of numerical results with a nonlinear autoregressive exogenous model (NARX) makes it possible to control system effectively by saving a significant amount of time.
Highlights
Buildings make up about 39% of the energy consumption in the United States in which heating, ventilation and air conditioning (HVAC) accounts for more than 40% of the proportion (Pérez-Lombard, Ortiz, & Pout, 2008).there have been increasing demands to design these equipment and systems and to control energy efficiency
Black box approach is defined by establishing a nonlinear relationship between data measured from input and output of a real device (Bourdouxhe, Lebrun & Grodent, 1998) In this regard, applying certain methods such as neural network, fuzzy logic, self-tuning and auto regressive models, researchers have defined accurate models
Availability limitation of coil input - output data and unpopularity of black box method cause the data needed in nonlinear autoregressive exogenous model (NARX) method be obtained by implicit method of numerical solution for dynamic equations
Summary
Buildings make up about 39% of the energy consumption in the United States in which heating, ventilation and air conditioning (HVAC) accounts for more than 40% of the proportion (Pérez-Lombard, Ortiz, & Pout, 2008).there have been increasing demands to design these equipment and systems and to control energy efficiency. Cooling, heating and dehumidifying are coils’ certain functions. Controlling these functions considerably affects thermal comfort and energy consumption in the buildings. Implementing an appropriate control approach requires a comprehensive and accurate model. Researchers have been using white and black box approaches to simulate coil performance. White box approach developed primary model on mass and energy balanced equations (Xin, Jin Wen, Theodore & Smith, 2005). Black box approach is defined by establishing a nonlinear relationship between data measured from input and output of a real device (Bourdouxhe, Lebrun & Grodent, 1998) In this regard, applying certain methods such as neural network, fuzzy logic, self-tuning and auto regressive models, researchers have defined accurate models
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