Multi-function partitioned design method for photovoltaic curtain wall integrated with vacuum glazing towards zero-energy buildings

Yutong Tan, Jinqing Peng, Zhengyi Luo, Yimo Luo, Tao Ma, Jie Ji, Hongxing Yang, Fazhi Wang and Minfeng Zhu

Renewable Energy, 2023, vol. 218, issue C

Abstract: The vacuum integrated photovoltaic (VPV) curtain wall has garnered widespread attention from scholars owing to its remarkable thermal insulation performance and power generation ability. However, there is a lack of in-depth, performance-driven optimal design that considers the mutually constraining functions of the VPV curtain wall. To address this issue, this study proposed a multi-function partitioned design method for VPV curtain walls aimed at reconciling the competing demand of different functions. Firstly, the VPV curtain wall was divided into daylight, view, and spandrel sections, and the corresponding models of each section with different PV coverages were developed in WINDOW software. Then, the opto-thermal characteristics of window models were exported to EnergyPlus and Radiance software for daylight and energy co-simulation. Finally, the optimal design of the partitioned VPV curtain wall was determined by employing the multiple criteria decision method, TOPSIS. The results indicated that the partitioned VPV curtain wall with 50%, 40%, and 90% PV coverages of daylight, view, and spandrel sections results in 82.8% useful daylight index, 62.7% hourly net-zero energy ratio, and 150.66 kWh surplus electricity. The study specified the contribution of each section to different performances and provided a new design method for the application of VPV curtain walls towards energy-efficient buildings.

Keywords: Vacuum integrated photovoltaic curtain wall; Multi-function partitioned optimal design; Net-zero energy potential; TOPSIS decision method (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:218:y:2023:i:c:s0960148123011722

DOI: 10.1016/j.renene.2023.119257

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