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Journal : International Journal of Renewable Energy Development

Multi-objective optimisation and sensitivity analysis of component influences on efficiency in air-based bifacial photovoltaic thermal systems (B-PVT) Rajani, Ahmad; Mat Said, Dalila; Noorden, Zulkarnain Ahmad; Ahmad, Nasarudin; Arifin, Muhammad Subhan; Komarudin, Udin; Atmaja, Tinton Dwi; Subagyo, Subagyo; Fudholi, Ahmad
International Journal of Renewable Energy Development Vol 13, No 4 (2024): July 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60212

Abstract

Bifacial Photovoltaic Thermal (B-PVT) technologies have seen significant advancements in sustainable energy production by converting solar energy into useful electric and thermal energies simultaneously. The present study explored the optimisation of these systems by first performing sensitivity analysis on design parameters to identify key variables affecting their performance efficiencies. The system design and performance were then studied simultaneously using a multi-objective optimisation algorithm NSGA-II. It was found that increasing packing factors from 0.4 to 0.8 leads to a 15% increase in both electrical and thermal efficiencies, while an asymmetry in channel depths could lead to an 8% increase in thermal efficiency.  Key design parameters such as transmissivity cover, mass flow rate, packing factors and channel depth ratios were found to have the most significant influence on overall system performance. Multi-objective optimisation of design variables results in a Pareto front describing trade-offs between solutions of conflicting objectives of performance. Optimisation with preferences towards overall efficiency over temperature differential produces solutions with a high overall efficiency yield of 70.79%, requiring specific values for mass flow rate (0.197 kg/s) and channel ratio (0.129), however at the expense of a reduced temperature differential of 5.12oC. Solutions with a balanced preference towards both objectives could produce a solution that is less biased in performance.