Numerical Simulation of Energy Systems to Control Environment Microclimate

Genco, Angela; Viggiano, Annarita; Viscido, Lucio; Sellitto, Giuseppe; Magi, Vinicio

doi:10.18280/ijht.34sp0249

Cited by 3 publications

(6 citation statements)

References 12 publications

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“…Specifically, the AC_Code model, developed and validated in Ref. [1], has been re-considered and two upgraded versions (AC_Code 2.0 and 3.0) are developed by implementing different control systems. In AC_Code 2.0, a control system with adjustable airflow rate and fixed thermo-hygrometric conditions at the inlet of the controlled environment is implemented, whereas in AC_Code 3.0 a control system with adjustable inlet temperature of the microclimate environment is provided.…”

Section: Discussionmentioning

confidence: 99%

“…The AC_Code for dynamic simulations of HVAC systems described in Ref. [1] was developed in C++ programming language. In this work, two upgraded versions of the model, named AC_Code 2.0 and AC_Code 3.0 respectively, are employed in order to analyze the behavior of air conditioning systems under different operating conditions.…”

Section: The Modelmentioning

confidence: 99%

“…A predictive mathematical model has been already developed in Ref. [1] in order to study the performance of the air conditioning systems for controlled microclimates. The authors provided an estimate of the energy consumptions in terms of heating/cooling and humidification/dehumidification energy and reheat (when such process occurs) and their model has been validated by comparing the results with those obtained by using TRNSYS-17, a commercial software for dynamic simulation, as described in Ref [2].…”

Section: Introductionmentioning

confidence: 99%

“…Starting from the predictive mathematical model AC_Code developed and validated in Ref. [1], two upgraded simulation models are presented. Such models take into account different airflow rate control systems and a detailed energy transfer balance of the conditioned environment.…”

Section: Introductionmentioning

confidence: 99%

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Optimization of microclimate control systems for air-conditioned environments

Genco¹,

Viggiano²,

Viscido³

et al. 2017

IJHT

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The optimization of the performance of air conditioning systems is mandatory in order to minimize costs by ensuring the attainment of specific thermo-hygrometric conditions of controlled environments at the same time. The aim of the present work is the analysis of the process parameters that play a fundamental role in the conditioning process of controlled microclimates. Starting from a predictive mathematical model that was developed to study the performance of air-conditioned environments, two upgrades are presented by implementing two separate control systems. The first one is based on an adjustable airflow rate and the other on an adjustable inlet temperature of the controlled environment. The first model estimates the energy consumption in terms of heating/cooling and humidification/dehumidification energy and reheat (when such process occurs) with an adjustable airflow rate computed by performing a heat transfer balance of the microclimate environment for a given inlet temperature. In the second model, the energy consumption is evaluated by keeping the airflow rate quasi-constant and adjusting the inlet temperature based on a thermal energy balance of the controlled environment. The results obtained with the two models have been compared under several climatic and set-point (comfort) conditions, thus assessing the advantages and disadvantages of both models.

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Section: Discussionmentioning

confidence: 99%

Section: The Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimization of microclimate control systems for air-conditioned environments

Genco¹,

Viggiano²,

Viscido³

et al. 2017

IJHT

Self Cite

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“…The control strategy of indoor relative humidity is mandatory in controlled microclimate to ensure the balance between the thermal load due to the occupants in exhibition areas and the latent load related to outdoor air humidity [8]. Analysis under different boundary conditions and control system HVAC has been carried out in [8][9][10]. Based on the same hourly climatic data source, the authors in [8] simulate a control system within a modern museum by using the dynamic simulation code DOE2.1.…”

Section: Introductionmentioning

confidence: 99%

How to enhance the energy efficiency of HVAC systems

Genco¹,

Viggiano²,

Magi³

2018

MMEP

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HVAC systems for controlled microclimate environments can be very energy consuming depending on the specific thermo-hygrometric conditions to be attained with respect to the conditions of external air. The aim of the present work is the analysis of some useful strategies devoted to reduce HVAC energy consumption. To this end, an in-house developed software is employed to evaluate energy consumption in terms of heating/cooling, humidification/dehumidification and reheat contributions. The test-case considered in this work is a museum environment where specific conditions are required to ensure long-term safety and preservation of the exhibitions by considering also visitors occupancy. The HVAC system is coupled with the exhibition room where the energy demand is computed through the microclimate energy balance. The simulation model has been validated by comparing the results in terms of energy demand to those obtained in the literature. Different strategies have been implemented to reduce the energy cost, i.e. a partial bypass of cooling coil, an increase of the accepted tolerance for the relative humidity set-point value, an improvement of the thermal insulation of the building and a recirculation of the microclimate air. The results obtained by adopting such strategies have been compared to assess the efficiency of HVAC systems.

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