Conference Editor
Jianshun Zhang; Edward Bogucz; Cliff Davidson; Elizabeth Krietmeyer
Keywords:
Simulation based optimization, PV-PCM modules, PCM type, Buildings energy savings.
Location
Syracuse, NY
Event Website
http://ibpc2018.org/
Start Date
24-9-2018 3:30 PM
End Date
24-9-2018 5:00 PM
Description
This paper reports the results of a genetic optimisation based numerical analysis of a PV-PCM system integrated into a double skin façade. The aim of the research activity was to develop and test the performance of a proposed simulation approach to identify the optimal configuration of the PCM layer, in terms of temperature transition range, and thickness, to assure the best energy performance of the façade system. Furthermore, because of the intimate relationship between the PCM’s features and the ventilated cavity to define the performance of the façade system, the domain of exploration included as variable the airflow rate and ventilation schedule. The evaluation of the performances of the PV-PCM glazed facade is carried through an onpurpose developed, transient 1-D (with finite difference method) heat transfer model, which integrates a suitable representation of the PCM’s system (through the so-called enthalpy method) to include the thermophysical behviour of such a type of materials. This numerical model is implemented in MATLAB and coupled to TRNSYS in order to calculate the dynamic thermal energy profiles of a fictitious building equipped with such a façade. The subsequent single objective optimization is based on a genetic algorithm, which looks for the best PCM type and schedule of ventilation in order to optimize the summer thermal energy performance in two case-study cities, Venice and Chicago. The results show how the proposed genetic optimisation algorithm is capable of identifying the most suitable configuration (that differs in each climate) after a relatively small number of generations (ca. 25). Furthermore, the optimisation approach used in this study leads to the identification of configurations capable of assuring a reduction in the cooling energy need (objective function) in the range 28% to 19 %, when compared to non-optimal configurations, for the two case-study cities.
Recommended Citation
Elarga, Hagar; Monte, Andrea Dal; Goia, Francesco; and Benini, Ernesto, "PV-PCM system integrated into a double skin façade. A Genetic optimization based study for the PCM type selection" (2018). International Building Physics Conference 2018. 4.
DOI
https://doi.org/10.14305/ibpc.2018.ms-3.04
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
PV-PCM system integrated into a double skin façade. A Genetic optimization based study for the PCM type selection
Syracuse, NY
This paper reports the results of a genetic optimisation based numerical analysis of a PV-PCM system integrated into a double skin façade. The aim of the research activity was to develop and test the performance of a proposed simulation approach to identify the optimal configuration of the PCM layer, in terms of temperature transition range, and thickness, to assure the best energy performance of the façade system. Furthermore, because of the intimate relationship between the PCM’s features and the ventilated cavity to define the performance of the façade system, the domain of exploration included as variable the airflow rate and ventilation schedule. The evaluation of the performances of the PV-PCM glazed facade is carried through an onpurpose developed, transient 1-D (with finite difference method) heat transfer model, which integrates a suitable representation of the PCM’s system (through the so-called enthalpy method) to include the thermophysical behviour of such a type of materials. This numerical model is implemented in MATLAB and coupled to TRNSYS in order to calculate the dynamic thermal energy profiles of a fictitious building equipped with such a façade. The subsequent single objective optimization is based on a genetic algorithm, which looks for the best PCM type and schedule of ventilation in order to optimize the summer thermal energy performance in two case-study cities, Venice and Chicago. The results show how the proposed genetic optimisation algorithm is capable of identifying the most suitable configuration (that differs in each climate) after a relatively small number of generations (ca. 25). Furthermore, the optimisation approach used in this study leads to the identification of configurations capable of assuring a reduction in the cooling energy need (objective function) in the range 28% to 19 %, when compared to non-optimal configurations, for the two case-study cities.
https://surface.syr.edu/ibpc/2018/MS3/4
Comments
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