Size Optimization and Performance Analysis of Hybrid Biogas-Solar System for Energy-Efficient Dairy Farming

In Bangladesh, dairy industry plays a pivotal role in country's economic growth. Which is why integrating Biogas with Solar Photovoltaic (PV) systems offers a reliable and sustainable energy solution for dairy farms. By supplementing solar energy in a hybridized setup, biogas ensures a consistent power supply, while also contributing to waste management and environmental sustainability. In this paper, area, load demand and biogas-solar generation potential in a conventional Bangladeshi dairy farm is studied. Then four renowned nature-inspired algorithms, Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), Artificial Hummingbird Algorithm (AHA), and Polar Fox Optimization Algorithm (PFOA) are applied to optimize the design parameters of a Hybrid Biogas-Solar System for the farm. The primary objectives of optimization are to minimize costs, maximize energy output, and promote self-sustainability in dairy farming. The simulation results revealed that the system provided by the Artificial Hummingbird Algorithm (AHA) achieved a levelized cost of energy (LCOE) of $0.045/kWh, a grid independent design with 0% loss of power supply probability (LPSP), and a payback period of 10 years and 4 months, making it the best-performing solution in terms of system reliability, self-sufficiency and energy efficiency compared to the GWO, WOA and PFOA.