Optimization assessment of the energy performance of a BIPV/T-PCM system using Genetic Algorithms

• Published in: Renewable energy Vol. 137; pp. 157 - 166
• Main Authors: Pereira, Ricardo, Aelenei, Laura
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.07.2019
• Subjects: algorithms; Building integrated photovoltaic/thermal; energy efficiency; Energy storage; Genetic Algorithm; model validation; Phase-change material; renewable energy sources; simulation models; summer; Thermal modelling; winter; Building integrated photovoltaic/thermal; Phase-change material; Genetic Algorithm; Energy storage; Thermal modelling
• ISSN: 0960-1481; 1879-0682
• DOI: 10.1016/j.renene.2018.06.118

In this paper, a BIPV/T-PCM installed in an office building façade is investigated to approach the system efficiency optimization using Genetic Algorithm method. Based on an updated mathematical model, theoretical simulation has been conducted for BIPV/T-PCM in this case for the existing system set-up (geometry-air cavity width, ventilation, system layers). Furthermore, field testing for this case has also been performed to validate the model, and then the simulated and experimental results are compared and found in considerably good agreement. The overall energy efficiency of the system was evaluated for winter and summer condition adopting different utilization strategies and optimization variables have been identified. The thermal and electric efficiencies were calculated based on the optimization variables and the results shown that the system can achieve a maximum overall efficiency of 64% with winter configuration and 32% with summer configuration. •Efficiency optimization of a BIPV/T-PCM using Genetic Algorithm approach is proposed.•A numerical model is presented and validated.•With optimization process the system can achieve a higher efficiency.