Integrated Hybrid Renewable Energy System Optimization for Sustainable Agricultural Operations

The reliance on traditional fossil fuels in agriculture leads to rising energy costs, environmental degradation, and vulnerability to climate change. Transitioning to renewable energy systems can provide cost savings, enhance sustainability, and improve resilience against energy supply disruptions. Embracing these technologies is essential for promoting efficient agricultural practices. Consequently, this paper proposes a mixed-integer linear programming model (MILP) for optimizing the configuration of hybrid photovoltaic, wind, and hydrogen renewable energy systems, with the objective of reducing the overall life cycle costs of greenhouse farms in Saudi Arabia. The model calculates the capacities of individual components, including photovoltaic (PV) modules, wind turbines, hydrogen storage tanks, fuel cells, and electrolyzers. The proposed model is solved using the General Algebraic Modeling System (GAMS) software. The results show that for a farm consisting of 20 greenhouses, employee accommodations, and a water treatment facility, the optimal system includes 552 PV panels (with a capacity of 150 W), 7 wind turbines (with a capacity of 10 kW), 6 fuel cells, 9 electrolyzers, and 2144 hydrogen tanks for storage (with a nominal capacity of 0.3 kWh). The annual energy cost is estimated at $100,527.84, with a levelized cost of energy (LCOE) of $0.056/kWh. The system also yields a reduction in CO₂ emissions of 903.631 tons per year, highlighting the potential of hydrogen as a feasible energy storage solution to mitigate fluctuations in renewable energy output. The findings demonstrate the viability of renewable energy in agricultural applications and emphasize the importance of hybrid configurations for energy efficiency. Future studies will explore the integration of other renewable resources and advanced optimization methods to further enhance cost savings and system performance.