Stochastic Techno-Economic Optimization of off-Grid Solar– Wind–Hydrogen–Battery Hybrid Renewable Energy Systems for Rural Electrification Using the Salp Swarm Algorithm

Ganiyu Adedayo Ajenikoko; Andrew Oyekanmi Oke; Adekunle Sarafadeen Jimoh; Abdulbasit Oladayo Ajenikoko; Muhammed Daramola Kolapo; Israel Damilare; Olukotun; Corresponding Author

doi:10.56201/ijcsmt.vol.12.no10.2026.pg167.180

Stochastic Techno-Economic Optimization of off-Grid Solar– Wind–Hydrogen–Battery Hybrid Renewable Energy Systems for Rural Electrification Using the Salp Swarm Algorithm

Ganiyu Adedayo Ajenikoko, Andrew Oyekanmi Oke, Adekunle Sarafadeen Jimoh, Abdulbasit Oladayo Ajenikoko, Muhammed Daramola Kolapo, Israel Damilare, Olukotun, Corresponding Author

Abstract

Planning dependable off-grid electricity for isolated settlements requires storage technologies capable of responding to both routine renewable fluctuations and prolonged low-generation periods. This study develops a stochastic techno-economic framework for a photovoltaic–wind–battery–hydrogen microgrid optimized using the Salp Swarm Algorithm . The architecture combines short-duration battery cycling with an electrolyser, hydrogen reservoir and fuel cell for longer-duration supply support. A constructed hourly demand and renewable-resource dataset represents approximately 600 kWh of community electricity use per day. Three planning scenarios, assigned probabilities of 0.60, 0.25 and 0.15, capture ordinary conditions, extended weak-resource episodes and elevated demand. Component capacities are selected to minimize probability-weighted levelized electricity cost while restricting unserved energy to 0.5% in each scenario. The financial assessment assumes a twenty-year project lifetime and an 8% real discount rate. The best feasible hydrogen-assisted design contains 44.4 kW of photovoltaic generation, 182.4 kW of wind capacity, 63.9 kWh of batteries, 154.3 kg of hydrogen storage, a 14.9 kW electrolyser and a 19.9 kW fuel cell. Its estimated net present cost is US$846,684 and its scenario-weighted electricity cost is US$0.394/kWh. Under the same modeled stress conditions, a battery-only alternative requires substantially greater electrochemical storage and reaches US$0.998/kWh. A design optimized only for normal conditions appears cheaper but experiences 8.38% unmet demand in the adverse-resource scenario. The comparisons indicate that long-duration hydrogen storage can provide planning value when multiday shortages dominate the reliability requirement, although its advantages depend strongly on equipment prices and wind quality. Sensitivity tests reveal significant reliability deterioration with moderate resource reductions or demand growth. The contribution is an integrated, reproducible scenario-constrained evaluation approach, not evidence of field performance. Validation with measured weather, demand, component-cost and safety data remains necessary before translating the findings into an investment decision. Further work should evaluate water requirements, electrolyser degradation, hydrogen safety and critical-load service reliability. IJCSMT

Keywords

Salp Swarm Algorithm; stochastic optimization; rural electrification; solar–wind microgrid; hydrogen energy storage; battery storage; techno-economic analysis.

References

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Stochastic Techno-Economic Optimization of off-Grid Solar– Wind–Hydrogen–Battery Hybrid Renewable Energy Systems for Rural Electrification Using the Salp Swarm Algorithm

Abstract

Keywords

References

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