Numerical analysis and ANN performance prediction of solar composite ventilation wall for built environment regulation

• Published in: Energy conversion and management Vol. 311; p. 118512
• Main Authors: He, Jian-Wei, Shu, Zheng-Yu, Huang, Ruo-Nan, Liu, Zi-Quan, Huang, Chang, Cai, Yang, Zhao, Fu-Yun
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.07.2024
• Subjects: Artificial neural network potential prediction; Climate and regional adaptation; Indoor air quality; Solar composite ventilation wall; Climate and regional adaptation; Artificial neural network potential prediction; Solar composite ventilation wall; Indoor air quality
• ISSN: 0196-8904; 1879-2227
• DOI: 10.1016/j.enconman.2024.118512

•Application potential study for different typical place with multiple climates.•A numerical model for heat regulation, purification and power generation.•Mechanism of heat-flow-purification-electricity has been numerically explored.•Predictions among the five places are given to extrude the practical values.•Highest annual total energy conversion at 1367.39 kWh is obtained in Guangzhou. With the aim to achieve winter heating, summer heat insulation and year-round power generation as well as indoor pollutant purification, photovoltaic (PV) combined with phase change heat storage technology is ingeniously embedded in an adjustable solar composite ventilation wall with entire room model (SPVW-PV/PCM) in this study. Then, the effects of key parameters e.g. PCM melting temperature Tm and PV coverage ratio Cr on solar energy conversion and utilization with indoor environment creation are comprehensively illustrated by indoor temperature, exergy efficiency as well as power generation amount. In addition, to further clarify the application potential of the proposed model applied in different typical places in China, the artificial neural network (ANN) has been rarely adopted to predict the annual heating amount, power generation as well as its economic and environmental benefits. Research results show that the three numerical submodels closely align with previously published results, with only minor discrepancies observed in the decoupling model regarding Cout, vroom and PCM melt fraction, well within acceptable numerical tolerances of 9.87% RMSE. The thermal performance is significantly influenced by the key parameters of Tm and Cr, with at least 110 min of advance heating start-up time revealed, and excellent indoor temperature improvement of 1.59 K and 3.02 K are achieved in the heating season at Tm = 318 K or Cr = 0 % simulated group. The highest annual total energy conversion of 1367.39 kWh is surveyed in Guangzhou, corresponding to the lowest levelized cost of electricity (LCOE) of 0.18 $/kWh and the highest CO2 saving cost of 19.03 $/year. The total energy conversion effect and the CO2 saving cost can be effectively improved by 13.88 % and 13.82 % in Guangzhou, respectively, compared to the coupling off-grid PV and conventional wall in building. These research findings offer valuable insights for optimizing the design of SPVW-PV/PVM in indoor environmental construction and enhancing its overall applicability.