ArticleScientific reports2026
Multi-objective sizing and performance optimization of islanded hybrid renewable microgrids: a case study in yanbu, Saudi Arabia.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Hybrid microgrid systems (HMS) integrating renewable energy sources (RESs) offer a sustainable solution for residential electrification in remote and arid regions. However, optimal sizing remains challenging due to the trade-offs between reliability, cost, and renewable penetration. This study proposes a multi-objective optimization framework for the techno-economic design of a HMS composed of solar photovoltaic (PV), wind turbine (WT), diesel generator (DG), and battery energy storage system (BESS) units for residential communities in Yanbu, Saudi Arabia. The system performance is evaluated under three load scenarios corresponding to 5, 10, and 15 houses. The optimization problem is formulated to minimize the loss of power supply probability (LPSP) and cost of energy (COE), while maximizing the renewable fraction (RF). Two advanced metaheuristic algorithms, Multi-Objective Salp Swarm Algorithm (MOSSA) and Multi-Objective Whale Optimization Algorithm (MOWOA), are employed and comparatively assessed. A rule-based energy management strategy is integrated to ensure reliable system operation. Results demonstrate that MOSSA provides broader Pareto front coverage and superior solution diversity, while MOWOA achieves competitive cost values in specific scenarios. For the light-load case (5 houses), the optimal PV/WT/BES/DG configuration using MOSSA achieves a COE of 0.45683 $/kWh with an LPSP of 2.0537%, ensuring high reliability. Under normal loading (10 houses), the optimal PV/WT/BES configuration using MOSSA yields a minimum COE of 0.16496 $/kWh, while the DG-integrated configuration reduces LPSP to 16.748% at a COE of 0.26128 $/kWh. For heavy loading (15 houses), the optimized PV/WT/BES/DG system achieves a COE of 0.20873 $/kWh with RF exceeding 88%, demonstrating scalability and strong renewable penetration. Increasing the number of houses leads to higher renewable penetration and reduced dependence on diesel generation. Overall, the proposed framework delivers a scalable and practically applicable solution for residential microgrid deployment in arid regions.
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