Results of the statistical analysis for case 2.

Renewable energy technologies offer promise for addressing energy access and environmental concerns, especially in remote off-grid areas. This paper presents a comprehensive techno-economic analysis of an off-grid PV/wind/biomass hybrid system. Employing optimization techniques including the osprey optimization algorithm (OOA), zebra optimization algorithm (ZOA), and flying foxes optimization (FFO) algorithm, the study aims to determine the optimal sizing of solar PV, wind, biomass, and battery components. Using data from Tabuk, Saudi Arabia (28.38° N, 36.56° E), the study seeks to achieve optimal sizing for solar PV, wind, biomass, and battery storage components to minimize the net present cost (NPC) and ensure reliable power supply, adhering to specified loss of power supply probability (LPSP) and excess energy thresholds. Three battery types, namely, flooded lead-acid, lithium iron phosphate (LFP), and nickel iron (Ni-Fe), were analyzed. Results reveal that ZOA outperformed other algorithms, supplying electricity at a minimum cost of 0.1285 $/kWh in one configuration, with the LFP battery achieving the lowest NPC of 3.8 M$ in case studies with constrained LPSP. Across multiple simulations, ZOA displayed superior stability and convergence characteristics, evidenced by its tight objective function range and lower relative error metrics. These findings underscore the potential of this integrated approach to enhance the economic viability and operational resilience of off-grid hybrid microgrid systems, particularly in arid and semi-arid regions.