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The aim of the present work is the development of a predictive mathematical model for the analysis and optimization of energy systems used to control the environment microclimate in industrial plants. This model provides not only the evaluation of the optimal configuration on the basis of different process parameters in the existing environments, but also the analysis and the prediction of the energy consumption of a plant during the design phase. The model describes the thermodynamics of conditioning processes and allows the evaluation of the influence of design variables and of hourly averaged weather conditions on energy consumption. The model is developed both in TRNSYS-17 and C ++ programming language such that it can also be used under MATLAB computing environment. The results obtained with the two models are compared under different climatic conditions in terms of heating/cooling and humidification/dehumidification energy consumption, thus assessing the accuracy of both models. The results obtained by using different set-point conditions under different climatic zones are also presented.

The aim of the present work is the development of a predictive mathematical model for the analysis and optimization of energy systems used to control the environment microclimate in industrial plants. This model provides not only the evaluation of the optimal configuration on the basis of different process parameters in the existing environments, but also the analysis and the prediction of the energy consumption of a plant during the design phase. The model describes the thermodynamics of conditioning processes and allows the evaluation of the influence of design variables and of hourly averaged weather conditions on energy consumption. The model is developed both in TRNSYS-17 and C ++ programming language such that it can also be used under MATLAB computing environment. The results obtained with the two models are compared under different climatic conditions in terms of heating/cooling and humidification/dehumidification energy consumption, thus assessing the accuracy of both models. The results obtained by using different set-point conditions under different climatic zones are also presented.

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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