Modeling and simulation of the heating circuit of a multi-functional building

Sangi, Roozbeh; Baranski, Marc; Oltmanns, Jens Uwe; Streblow, Rita; Müller, Dirk

doi:10.1016/j.enbuild.2015.10.027

Cited by 26 publications

(10 citation statements)

References 4 publications

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“…Moreover, the heating and cooling demands of the building are covered through low‐temperature heating and high‐temperature cooling networks using a variety of energy supply technologies such as Façade Ventilation Unit (FVU), Active Chilled Beam (ACB), Concrete Core Activation (CCA), Underfloor Heating (UFH), etc. For more information about the energy concept of the building see References and .…”

Section: Case Studymentioning

confidence: 99%

Splitting the dynamic exergy destruction within a building energy system into endogenous and exogenous parts using measured data from the building automation system

2020

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Summary This study presents a novel approach to apply advanced exergy analysis to a dynamic system. The main building of the E.ON Energy Research Center located in Aachen, Germany, which is a large, complex and multifunctional building is considered as the case study. Results of the present study show a substantial interdependency among different components of the considered building, meaning that a significant improvement in the overall performance of the building could be achieved through the implementation of a better control algorithm. Furthermore, it is shown that the improvement suggestions and optimization priorities obtained from an advanced exergy analysis are more rational and reasonable compared with a conventional exergy analysis. For instance, based on the results of this study, the Façade ventilation units and the active chilled beams in the cooling network of the considered building cause a large amount of exergy destruction in other components of the system. So, based on an advanced exergy analysis these components have the highest priority for optimization. Improvement of these components not only decreases the endogenous exergy destruction within them but also results in lower (exogenous) exergy destructions in the remaining components of the system. In a conventional exergy analysis, however, only exergy destructions within system components are calculated and the influence of components on each other cannot be obtained.

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Section: Case Studymentioning

confidence: 99%

Splitting the dynamic exergy destruction within a building energy system into endogenous and exogenous parts using measured data from the building automation system

2020

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“…The first step includes using some applicable tools from the field of system projecting determined for identification an existing or planned system within the real world and, consequently, transforming the identified system into a mathematic model form (Sangi et al, 2016). This form should take into consideration the above mentioned analogy between electronic and heat circuits for physical parameters to be definitely assigned and processed by the analytic software.…”

Section: Mathematic Model Constructionmentioning

confidence: 99%

“…The temperature values and their time courses are the most important quantities for state changes examining in the given points and, therefore, the equation (17) must be adjusted so that the heating nods matrix would be in the left side: (18) or in the full form: (19) where …”

Section: (17b)mentioning

confidence: 99%

System Macromodel of Agricultural Building with Aim to Energy Consumption Minimization

Malinovský

2018

AOL

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Economizing on energy intended for heating of agricultural buildings is correlative with their convenient construction from the viewpoint of both thermal and mechanical properties. Therefore, knowledge of temperature time characteristics enables building construction optimizing. This paper deals with process of recognizing elements and parameters of some particular building object, assembling its system macromodel, and analysing temperature time characteristics on its base using appropriate mathematic tools (Laplace and Fourier transformation, matrix characterizing of model parameters) and special software (ANATH). Finally, the resulting temperature time characteristics can be used for an optimal design of some planned agricultural object or for reconstruction of some existing one. KeywordsEconomy of agricultural engineering, heating energy economy, system analysis, temperature time characteristics, expenses optimizing, ambient temperature well-being.

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“…thermal mass of the floor is calculated as: Volume of the floor = length  width  height = 12  2.4  0.075 = 2.16 m 3 Density of concrete = = 2300 kg/ m 3 mass = M = 2.16  2300 = 4968 kg specific heat of concrete = Cp = 880 J/kg.K heat transfer = Ph = MCpT = 4968  880  T = 4371840TT = Ph/4371840 ……….…….…… (8). …”

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confidence: 99%

Modelling and Simulation of Underfloor Heating System Supplied from Heat Pump

Akmal

Fox

2016

2016 UKSim-AMSS 18th International Conference on Computer Modelling and Simulation (UKSim)

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This paper describes thermal capacity and thermal inertia of an underfloor heating system supplied from a heat pump. A MATLAB/SIMULINK based thermal model of the system have been developed and presented with detailed mathematical equations. For this purpose, experimental results and actual measurements are used to model the energy storage and temperatures. The parameters used for the model are temperature, power and energy consumption, time constant and real-time. Hence, this model can be used to find building temperature variations, heat energy production, electrical energy consumption, instantaneous power, coefficients of performance on a real-time scale based on different control strategies used for demand side management. The developed model in SIMULINK includes the effect of thermal storage in the underfloor heating arrangement as well as the thermal mass of the building itself. Heat loss calculations were carried out to develop this model. The paper also employs different control strategies for operating the developed model.

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Modeling and simulation of the heating circuit of a multi-functional building

Cited by 26 publications

References 4 publications

Splitting the dynamic exergy destruction within a building energy system into endogenous and exogenous parts using measured data from the building automation system

Splitting the dynamic exergy destruction within a building energy system into endogenous and exogenous parts using measured data from the building automation system

System Macromodel of Agricultural Building with Aim to Energy Consumption Minimization

Modelling and Simulation of Underfloor Heating System Supplied from Heat Pump

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