In this paper, a model that analyses the coupling of a concentrating photovoltaic and thermal (CPV/T) system with a desiccant cooling (DC) system used to satisfy the energy loads required by a supermarket, is presented. A detailed analysis of the supermarket electrical and thermal loads is conducted in different periods of the year: summer, winter and half seasons. A CPV/T system linear focus configuration is considered, and its sizing as a function of the solar Direct Normal Irradiance (DNI) is realized for each period of the year. Hence, an Artificial Neural Network (ANN) is used to model carefully the DNI adopting experimental data in the simulation process. The coupling between the CPV/T and DC systems allows to obtain energy and economic savings during the year compared with a conventional solution, considering accurately in the modelling: supermarket energy loads, solar radiation, environmental conditions, etc. In particular, the analysis of three case studies is performed, where the main aim has been to size the CPV/T-DC integrated system and to study how it can match the different supermarket energy needs. The three solutions are analyzed from an energetic and economic point of view in order to demonstrate the effectiveness of the solution proposed.

Evaluation of the optimal thermal insulation thickness for an office building in different climates by means of the basic and modified “cost-optimal” methodology

D'Agostino D.;Marino C.;Minichiello F.
2019

Abstract

In this paper, a model that analyses the coupling of a concentrating photovoltaic and thermal (CPV/T) system with a desiccant cooling (DC) system used to satisfy the energy loads required by a supermarket, is presented. A detailed analysis of the supermarket electrical and thermal loads is conducted in different periods of the year: summer, winter and half seasons. A CPV/T system linear focus configuration is considered, and its sizing as a function of the solar Direct Normal Irradiance (DNI) is realized for each period of the year. Hence, an Artificial Neural Network (ANN) is used to model carefully the DNI adopting experimental data in the simulation process. The coupling between the CPV/T and DC systems allows to obtain energy and economic savings during the year compared with a conventional solution, considering accurately in the modelling: supermarket energy loads, solar radiation, environmental conditions, etc. In particular, the analysis of three case studies is performed, where the main aim has been to size the CPV/T-DC integrated system and to study how it can match the different supermarket energy needs. The three solutions are analyzed from an energetic and economic point of view in order to demonstrate the effectiveness of the solution proposed.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11588/762563
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