Novel techno-economic feasibility study of an off-grid PV/wind/diesel/battery hybrid energy system using MATLAB-HOMER link

• A novel off-grid PV/Wind/Diesel/Battery hybrid energy system is developed and optimized for remote regions in Sharurah, Saudi Arabia, targeting minimum cost and high renewable energy penetration. • The study evaluates the performance of multiple configurations using three dispatch strategies—Cycle Charging (CC), Load Following (LF), and a proposed MATLAB-linked (ML) strategy—based on Net Present Cost (NPC) and Cost of Energy (COE). • A detailed sensitivity analysis is performed to assess the impact of diesel fuel price variations on system cost and performance. • The optimized system demonstrates high renewable fraction, reduced emissions, and strong environmental benefits, offering a sustainable solution for off-grid applications. This paper investigates the design and optimization of an off-grid hybrid renewable energy system (HRES) for remote areas, combining solar PV, wind turbines, diesel generators, and battery storage. The system is analyzed using a proposed HOMER Pro with a MATLAB-linked dispatch strategy to evaluate technical feasibility and cost-effectiveness under varying weather conditions. A case study in Sharurah, Saudi Arabia, demonstrates the optimal configuration, which includes 5.8 MW of solar PV, 3.2 MW of wind turbines, 4 MWh of battery storage, and 2 MW of diesel backup. The proposed system achieves 100 % renewable energy penetration under optimal conditions, covering 328 % of the annual load demand (14,500 MWh) while generating 41 % excess electricity. Economically, the system yields a Net Present Cost (NPC) of $16.4 million, eliminating fuel costs and reducing CO 2 emissions by 1200 tons/year. Reliability is ensured with less than 0.1 % unmet load, making it a viable solution for sustainable energy supply in isolated regions. The results highlight the system’s ability to balance cost, reliability, and environmental benefits, proving its suitability for off-grid applications.