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The analysis and design of a small isolated power system (SIPS) with renewable energy sources (RES) and storage can be challenging, because of the large number of design options and the uncertainty in key parameters. RES add further complexity because their power output may be intermittent, seasonal and non-dispatchable. Owing to this characteristic, reliability evaluation of a RES-based SIPS cannot be implemented using the traditional deterministic and analytical methods. Moreover, this evaluation has to be done within a cost-benefit framework. This study models and investigates the effect of customer worth of interrupted supply (customer damage cost) on the optimal design of SIPS with storage and increased RES penetration. The SIPS optimal design is implemented with a genetic algorithm combined with local search procedure. In addition, this study examines the effect of the forced outage rate of SIPS components on SIPS optimal design via Monte Carlo simulation. The performance of the proposed hybrid optimisation methodology is investigated for a large number of alternative scenarios via sensitivity analysis, which study the effect on the results because of the uncertainty on weather data, components efficiency and cost data. The results show that the optimal design of a RES-based SIPS depends largely on the consideration of customer damage cost as well as the inclusion of components forced outage rate. The method and results presented in this article should be valuable in planning and operating SIPS with RES.