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@article{185457,
        author = {Tilak Singh and Shweta Singh and Manoj Verma and Ravi Kumar Kanaujia},
        title = {Design and Optimization of Solar-Wind Hybrid Systems for Electrifying Rural Areas},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {5},
        pages = {1528-1534},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=185457},
        abstract = {The study optimizes a solar PV–wind hybrid system for rural electrification, aiming to provide reliable and cost-effective power to remote communities with limited grid access. By combining solar and wind resources, the system ensures continuous electricity despite daily and seasonal variations. Optimization focuses on minimizing Levelized Cost of Energy (LCOE) or Net Present Cost (NPC) while maintaining high reliability (LPSP < 5%). The approach includes site-specific resource assessment, detailed load profiling, and modeling of PV, wind, and battery components. Metaheuristic optimization techniques, such as Genetic Algorithms and Particle Swarm Optimization, identify optimal system configurations, with sensitivity analyses addressing resource variability, cost changes, and load growth. Practical factors like component availability, maintenance, environmental resilience, and socio-economic impact are also considered. The optimized system can reduce fossil fuel dependence, lower carbon emissions, and improve rural living standards by supporting essential services and small-scale enterprises.},
        keywords = {Solar Photovoltaic (PV), Wind Energy, Hybrid Energy System, Rural Electrification, Levelized Cost of Energy (LCOE), Net Present Cost (NPC), Loss of Power Supply Probability (LPSP), Renewable Energy Optimization, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Energy Storage, Load Profiling, Sustainability, Carbon Emission Reduction.},
        month = {October},
        }