Development, investigation and Graywolf algorithm-assisted tri- objective optimization of a hybrid renewable-driven HVAC/power system.
The rising energy demand of the building sector has led to a critical need for innovative solutions to curb its 37 % share of global CO₂ emissions in 2020. This study introduces a novel hybrid energy system integrating solar photovoltaic-thermal (PVT) panels with a biofuel-driven boiler, designed to meet residential heating, cooling, and electricity needs. Dynamic simulations were conducted using TRNSYS to evaluate the system s real-world performance across varying climatic conditions. Optimization using the greywolf algorithm achieved a balance among three competing objectives: thermodynamic efficiency, environmental sustainability, and economic viability. The system delivered a thermal efficiency of 28.5 %, a levelized energy cost of 0.163 $/kWh, and a CO₂ emission index of 121 kg/MWh, reflecting significant improvements of 13.5 %, 23.1 %, and 15.4 %, respectively, over the baseline design. Unlike prior studies, this work uniquely combines dynamic transient modeling with multi-objective optimization for a solar-biofuel energy system, offering actionable insights into sustainable energy integration for the building sector. These findings underscore the system s potential to enhance energy performance while reducing environmental and economic costs. https://www.sciencedirect.com/science/article/abs/pii/ S2352710225001512