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.

Comments

If you are experiencing accessibility issues with this item, please contact the Accessibility and Inclusion Librarian through lib-accessibility@syr.edu with your name, SU NetID, the SURFACE link, title of record, and author & and reason for request.

DOI

https://doi.org/10.14305/ibpc.2018.ms-3.04

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.

COinS
 
Sep 24th, 3:30 PM Sep 24th, 5:00 PM

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

 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.