<![CDATA[Hybrid energy systems are increasingly vital in ensuring uninterrupted power delivery in remote or solar-dependent regions. This study addresses the operational challenges in such systems under failure scenarios by integrating advanced optimization techniques. This paper presents a failure-tolerant optimization approach for dispatching power in off-grid hybrid energy systems comprising solar, battery, and fuel generator sources. The objective is to ensure reliable energy delivery under failure conditions using Particle Swarm Optimization (PSO). A comparative analysis with a conventional greedy algorithm reveals that PSO significantly reduces unmet demand, particularly under critical component outages. The system is modeled in MATLAB/Simulink, simulating three failure scenarios—solar, battery, and fuel. The comparison between PSO and the greedy dispatch method was carried out using unmet load percentage, fuel consumption, and reliability index as key evaluation metrics, with the PSO executed for 50 iterations using 30 particles to ensure convergence. Results show that the PSO dispatcher achieved unmet energy reductions from 59.61% to 17.01% in fuel failure cases while minimizing fuel usage during renewable outages. The study concludes that PSO offers a promising solution for resilient energy management in isolated or rural microgrids.]]>
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